# Set the current wavelength to 800nm, wait for the motor to stop rotating, and then turn it off to tamp down the noise.
device.motorEnable = True
device.wavelength = startWavelength
device.waitForMotor()
times = np.linspace(0, modulationPeriodsPerMeasurement / fModulation,
samplesPerMeasurement) # ms
for wavelength in wavelengthsToMeasure:
device.motorEnable = True # Enable the motor for movement
device.wavelength = wavelength
device.waitForMotor()
device.motorEnable = False
data = device.Measure()
voltages = twosToVoltage(data)
syncPulseLocations = twosToInteger(device.getSyncData())
maximaSampleLocations = np.array(syncPulseLocations +
voltageMaximaDelaySamples,
dtype=np.int)[0:-3]
minimaSampleLocations = np.array(syncPulseLocations +
voltageMinimaDelaySamples,
dtype=np.int)[0:-3]
maxima = voltages[maximaSampleLocations]
minima = voltages[minimaSampleLocations]
Vpps = maxima - minima
averageVpp = np.mean(Vpps)
current = averageVpp / TIAResistance * 1e9 / 2 # current in nA, need the 2 because we have gain now.
currents = np.append(currents, current)
print(f'l: {wavelength}nm: {current:.2f}nApp')
samplingFrequency = 125 # 125kHz is the actual measured sampling rate, correct within 1Hz.
samplingPeriod = 1 / samplingFrequency
averaged = False
window = 'hann' # hann or boxcar
signalAmplitudeVpp = 0.05 # Volts
signalFrequency = 1 # kHz
device = SCPIDevice()
device.Configure(desiredMeasurements)
startSystemTime = time.perf_counter()
rawData = device.Measure()
endSystemTime = time.perf_counter()
deltaSystemTime = endSystemTime - startSystemTime
voltages = twosToVoltage(rawData)
dcOffset = np.mean(voltages)
# Set up our hanning / boxcar window
if window == 'hann':
energyCorrectionFactor = 1.633156
windowData = energyCorrectionFactor * scipy.signal.windows.hann(desiredMeasurements)
elif window == 'boxcar':
energyCorrectionFactor = 1
windowData = np.ones(desiredMeasurements)
voltagesFFTPowerOneSidedVrms = 4*np.square(np.abs(np.fft.fft((voltages-dcOffset)*windowData)))[0:halfDesiredMeasurements]
frequencies = np.arange(0, samplingFrequency/2, samplingFrequency/2/halfDesiredMeasurements)
theoreticalData = np.sin(2*np.pi*signalFrequency)
totalTransimpedance = 2 * TIAResistance
currents = np.array([])
# Set the current wavelength to 800nm, wait for the motor to stop rotating, and then turn it off to tamp down the noise.
device.motorEnable = True
device.wavelength = startWavelength
device.waitForMotor()
for wavelength in wavelengthsToMeasure:
device.motorEnable = True # Enable the motor for movement
device.wavelength = wavelength
device.waitForMotor()
device.motorEnable = False
data = device.Measure()
voltages = correctionFactor * twosToVoltage(data)
voltagePowerSpectrum = np.square(
np.abs(np.fft.fft(voltages / len(voltages))))
# Multiply by 2 to convert to single-sided spectrum
voltageSignalPower = voltagePowerSpectrum[signalBin] * 2
# Multiply by 2 to convert from RMS power into amplitude
voltageSignalAmplitude = np.sqrt(voltageSignalPower * 2)
# Multiply by 2 to convert to uApp instead of uA amplitude
currentSignalAmplitudeuApp = voltageSignalAmplitude / totalTransimpedance * 2
currentSignalAmplitudenApp = currentSignalAmplitudeuApp * 1e3
currents = np.append(currents, currentSignalAmplitudenApp)
print(f'{wavelength} nm: {currentSignalAmplitudenApp:.2f}')
device.motorEnable = True
device.wavelength = startWavelength # set our device back to the original wavelength
