def GetFr(sweepdata_folder, sweepdata_file, IQCalibrationfile, IQReffolder, IQReffilename):
### Read IQ Sweep data
freq, I, Q = reader.ReadSweep(sweepdata_folder, sweepdata_file)
### Get IQ Mixer calibration data for sweep data frequency
paras = IQ.IQ_GetPara(IQCalibrationfile, int(round(freq[len(freq)/2]/1e6)))
### Calibrate IQ Sweep data
I_mixercalibrated, Q_mixercalibrated = IQ.IQ_CorrtBarends(paras,I,Q)
### Normalize calibrated IQ Sweep data to IQ reference data
### Get complex IQ
IQ_normalized = IQ.IQ_Normalize_Sweep(freq, I_mixercalibrated, Q_mixercalibrated, IQReffolder, IQReffilename)
x_c, x_c_err, y_c, y_c_err, radius, radius_err, circle_fit_report, theta0, theta0_err, fr, fr_err, Qr, Qr_err, Qc, Qc_err, Qi, Qi_err, fit_report_phase = Fit_IQ_Sweep(freq, IQ_normalized)
return int(round(fr))
plt.figure(figsize=(18.5, 10.5))
for n in range(0, num):
### Get file name and resonance frequency
sweepdata_file = sweeplist[n]
noisedata_file = noiselist[n]
resfreq = float(resfreqlist[n])
# Read data
sweepfreq, sweepI, sweepQ = reader.ReadSweep(data_folder, sweepdata_file)
fsample, number, noiseI, noiseQ = reader.ReadNoise(data_folder,
noisedata_file)
meastime = len(number) / float(fsample)
# Get IQ Mixer calibration parameter
resfreqinMHz = int(round(sweepfreq[len(sweepfreq) / 2] / 1e6))
paras = IQ.IQ_GetPara(IQCalibrationfile, resfreqinMHz)
# Calibrate IQ data
I_mixercalibrated, Q_mixercalibrated = IQ.IQ_CorrtBarends(
paras, sweepI, sweepQ)
noiseI_mixercalibrated, noiseQ_mixercalibrated = IQ.IQ_CorrtBarends(
paras, noiseI, noiseQ)
# Normalize calibrated IQ Sweep data to IQ reference data
# Get complex IQ
sweepIQ_normalized = IQ.IQ_Normalize_Sweep(sweepfreq, I_mixercalibrated,
Q_mixercalibrated, IQReffolder,
IQReffilename)
noiseIQ_normalized = IQ.IQ_Normalize_Noise(resfreq, noiseI_mixercalibrated,
noiseQ_mixercalibrated,
IQReffolder, IQReffilename)
import numpy as np
import matplotlib.pyplot as plt
import IQMixer.IQCalib as IQ
import Analyse_PSD as PSD
import FileReader as reader
IQCorrectionfile = 'IQMixer_Calib/20160803_1M_BOX/EllipseFit_0dBm_2000MHz_8000MHz.csv'
folder = '../../../MeasurementResult/'
filename = 'Noise_19dBm_4000MHz_2000K_1S_2'
freq = 4000
fs, num, I, Q = reader.ReadNoise(folder, filename)
paras = IQ.IQ_GetPara(IQCorrectionfile, freq)
Icrr, Qcrr = IQ.IQ_CorrtBarends(paras, I, Q)
IQ = (Icrr + 1j * Qcrr) / np.sqrt(np.mean(Qcrr)**2 + np.mean(Icrr)**2)
revisetheta = -np.arctan2(np.mean(IQ.imag), np.mean(IQ.real))
noisecompfinalrevised = IQ * np.exp(1j * revisetheta)
fx, Pxx, fy, Pyy, fxy, Pxy = PSD.Full_Spectrum(IQ.real, IQ.imag, fs)
fxr, Pxxr, fyr, Pyyr, fxyr, Pxyr = PSD.Full_Spectrum(
noisecompfinalrevised.real, noisecompfinalrevised.imag, fs)
plt.plot(fx, 10 * np.log10(Pxx), label='ONres Amplitude ')
plt.plot(fy, 10 * np.log10(Pyy), label='ONres Phase')
plt.plot(fxr, 10 * np.log10(Pxxr), label='Ir')
plt.plot(fyr, 10 * np.log10(Pyyr), label='Qr')
plt.xscale('log')
plt.legend()
plt.show()
import IQMixer.IQCalib as IQ
import numpy as np
import FileReader as reader
from matplotlib.backends.backend_pdf import PdfPages
IQCorrectionfile = 'IQMixer_Calib/20160803_1M_BOX/EllipseFit_0dBm_2000MHz_8000MHz.csv'
"""
Edit folder and file name and measurement frequency in nnnn MHz
"""
cosraydata_folder = "../../../MeasurementResult/20160814_Al_Noguchi/CosmicRay/4579/"
freq = 4579
cosraydata_file = '2000K_0.5S_9624'
### Calibrate IQ data and calculate amplitude of IQ (IQ)
fs, num, I, Q = reader.ReadCosmicRay(cosraydata_folder, cosraydata_file)
paras = IQ.IQ_GetPara(IQCorrectionfile, freq)
I_mixercalibrated, Q_mixercalibrated = IQ.IQ_CorrtBarends(paras, I, Q)
IQ = np.sqrt((I_mixercalibrated - np.mean(I_mixercalibrated))**2 +
(Q_mixercalibrated - np.mean(Q_mixercalibrated))**2)
### Get index of maximum point and
### cut measurement data 500 points left from the peak and
### 2500 points right from the peak
numleft = 500
numright = 2500
index = IQ.argmax()
Ievent = I_mixercalibrated[index - numleft:index + numright]
Qevent = Q_mixercalibrated[index - numleft:index + numright]
amplitude = np.asarray(IQ[index - numleft:index + numright])
phase = np.arctan2(Qevent, Ievent)
cosraydata_folder = "../../../MeasurementResult/20160814_Al_Noguchi/CosmicRay/4579/"
freq = 4579
cosraydata_file = '2000K_0.5S_9624'
### Calibrate IQ data and calculate amplitude of IQ (IQ)
fs, num, I, Q = reader.ReadCosmicRay(cosraydata_folder, cosraydata_file)
paras = IQ.IQ_GetPara(IQCorrectionfile, freq)
I_mixercalibrated, Q_mixercalibrated = IQ.IQ_CorrtBarends(paras,I,Q)
IQ = np.sqrt((I_mixercalibrated-np.mean(I_mixercalibrated))**2 + (Q_mixercalibrated-np.mean(Q_mixercalibrated))**2)
### Get index of maximum point and
### cut measurement data 500 points left from the peak and
### 2500 points right from the peak
numleft = 500
numright = 2500
index = IQ.argmax()
Ievent = I_mixercalibrated[index-numleft:index+numright]
Qevent = Q_mixercalibrated[index-numleft:index+numright]
amplitude = np.asarray(IQ[index-numleft:index+numright])
phase = np.arctan2(Qevent, Ievent)
### Transfer number to time with microsecond unit
t = num[index-numleft:index+numright] / fs * 1e6
a, a_err, A, A_err, t0, t0_err, tau, tau_err, taur, taur_err, fit_report, residual = Fitter.Fit_CosmicRay(t, amplitude)
fitresult = Fitter.Fit_CosmicRay_model(t, t0, a, A, tau, taur)
### Plot data and fitting result and residual
font = {'family': 'serif',
'color': 'darkred',
'weight': 'normal',
'size': 10,
### Get IQ measurement data
data = []
with open(folder + filename + '.csv', 'r') as f:
for line in f:
data.append(map(str, line.split(',')))
frequency = np.asarray(
[int(float(data[i][0]) / 1e6) for i in range(0, len(data))])
I = np.asarray([float(data[i][1]) for i in range(0, len(data))])
Q = np.asarray(
[float(data[i][2].replace("\n", "")) for i in range(0, len(data))])
print frequency[0]
### IQMixer calibration file to correct data measured with IQMixer
# If the BOX is changed, please calibrate IQMixer again
IQCorrectionfile = 'IQMixer_Calib/20160803_1M_BOX/EllipseFit_0dBm_2000MHz_8000MHz.csv'
Icrr = []
Qcrr = []
for i in range(0, len(frequency)):
paras = IQ.IQ_GetPara(IQCorrectionfile, frequency[i])
Itemp, Qtemp = IQ.IQ_CorrtBarendsSingle(paras, I[i], Q[i])
Icrr.append(Itemp)
Qcrr.append(Qtemp)
### save calibrated result
crrfile = open(folder + filename + '_IQMixerCalibrated.csv', 'w')
fwrite = csv.writer(crrfile)
for i in range(0, len(Icrr)):
fwrite.writerow([frequency[i], Icrr[i], Qcrr[i]])
crrfile.close()
import numpy as np
import csv
import matplotlib.pyplot as plt
import IQMixer.IQCalib as IQ
import Analyse_Fit_SingleKID as FitSingle
import Analyse_PSD as PSD
import FileReader as reader
IQCorrectionfile = 'IQMixer_Calib/20160803_1M_BOX/EllipseFit_0dBm_2000MHz_8000MHz.csv'
sweepdata_folder = "../../../MeasurementResult/20160814_Al_Noguchi/"
sweepdata_file = 'Sweep_4579MHz'
freq, I, Q = reader.ReadSweep(sweepdata_folder, sweepdata_file)
paras = IQ.IQ_GetPara(IQCorrectionfile, int(round(freq[len(freq) / 2] / 1e6)))
I_mixercalibrated, Q_mixercalibrated = IQ.IQ_CorrtBarends(paras, I, Q)
#### CUT ####
bandwidth = 1e6
freq, real, imag = reader.CutSweep(bandwidth, freq, I_mixercalibrated,
Q_mixercalibrated)
comp = np.asarray([real[i] + imag[i] * 1j for i in range(0, len(real))])
### Fit ###
tau = 45e-9
a, a_err, alpha, alpha_err, tau, tau_err, phi0, phi0_err, fr, fr_err, Qr, Qr_err, Qc, Qc_err, Qi = FitSingle.Fit_7parameterIQ1(
freq, comp, tau)
fitIQ1 = a * np.exp(1j * alpha) * np.exp(
-2 * np.pi * 1j * freq * tau) * (1 - (Qr / Qc * np.exp(1j * phi0)) /
(1 + 2 * 1j * Qr * (freq - fr) / fr))
comptilt = comp * np.exp(2 * np.pi * 1j * freq * tau)
plt.axis('equal')
plt.plot(I_mixercalibrated, Q_mixercalibrated, 'b')
import numpy as np
import csv
import matplotlib.pyplot as plt
import IQMixer.IQCalib as IQ
folder = ''
filename = 'EllipseFit_-19dBm_3000MHz_3000MHz'
RF_Power = '-19dBm'
RF_Freq_Start = 3000 # MHz
RF_Freq_Interval = 10 # MHz, RF measurement sample every 10 MHz
Frequency = 3000
paras = IQ.IQ_GetPara(folder, filename,
(Frequency - RF_Freq_Start) / RF_Freq_Interval)
### Get IQ measurement data
data_file = 'Noise_17dBm_3000MHz_100K_1S_1'
data = []
with open(data_file + '.csv', 'r') as f:
for line in f:
data.append(map(str, line.split(',')))
freq = [float(data[i][0]) for i in range(0, len(data))]
I = [float(data[i][1]) for i in range(0, len(data))]
Q = [float(data[i][2].replace("\n", "")) for i in range(0, len(data))]
Icrr, Qcrr = IQ.IQ_CorrtBarends(paras, I, Q)
plt.plot(0, 0, '.')
plt.plot(I, Q, '.')
plt.plot(Icrr, Qcrr, '.')
#plt.show()
data.append(map(str,line.split(',')))
freq = [float(data[i][0]) for i in range(0,len(data))]
I = [float(data[i][1]) for i in range(0,len(data))]
Q = [float(data[i][2].replace("\n", "")) for i in range(0,len(data))]
Icrr, Qcrr = IQ.IQ_CorrtBarends(paras,I,Q)
plt.plot(0,0,'.')
plt.plot(I,Q,'.')
plt.plot(Icrr,Qcrr,'.')
#plt.show()
delay_time = 50e-9
for i in range(0,len(Icrr)):
Icrr[i] = ((Icrr[i]+1j*Qcrr[i]) * IQ.cable_delay_calib(delay_time,3e9)).real
Qcrr[i] = ((Icrr[i]+1j*Qcrr[i]) * IQ.cable_delay_calib(delay_time,3e9)).imag
### save calibrated result
folder2= ''
crrfile = open(folder2 + data_file + '_IQDelaycalibrated.csv', 'w')
fwrite = csv.writer(crrfile)
for i in range(0, len(Icrr)):
fwrite.writerow([Icrr[i], Qcrr[i]])
crrfile.close()
plt.plot(0,0,'.')
plt.plot(Icrr,Qcrr)
plt.show()