Fitting function for QUAK/ESR bias amplifiers

characterizs.py

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

from time import sleep

from pymso5000.mso5000 import MSO5000
from pyka3005p.ka3005pserial import KA3005PSerial

scanchannel = 2
nScans = 5
scanrange = np.linspace(0, 10, 11*10)

with MSO5000(address = "10.0.0.123", useNumpy = True) as mso:
	mso.set_channel_enable(scanchannel, True)
	with KA3005PSerial('/dev/ttyU0', False) as psu:
		fig, ax = plt.subplots(2, figsize=(6.4*10, 4.8*2*10))

		psu.setVoltage(0)
		psu.setCurrent(0.1)
		sleep(0.5)
		psu.setChannelEnable(True)

		# Now run nScans scans
		voltagesIn = scanrange
		voltagesOut = np.zeros((nScans, len(voltagesIn)))
		voltagesOutStd = np.zeros((len(voltagesIn),))
		voltagesOutMean = np.zeros((len(voltagesIn),))

		for iScan in range(nScans):
			for iPoint, pt in enumerate(voltagesIn):
				psu.setVoltage(pt)
				sleep(0.5)
				# Measure on MSO
				mso.force_trigger()
				sleep(0.2)
				data = mso.query_waveform(scanchannel-1, stats = [ "mean" ])

				# Why does stats = mean not work?!?!
				voltagesOut[iScan, iPoint] = np.mean(data['y'])

			ax[0].plot(voltagesIn, voltagesOut[iScan], label = f"Scan {iScan}")

		for iP in range(len(voltagesIn)):
			voltagesOutStd[iP] = np.std(voltagesOut[:,iP])
			voltagesOutMean[iP] = np.mean(voltagesOut[:,iP])

		data = {
			"voltageIn" : voltagesIn,
			f"voltageOut{scanchannel}raw" : voltagesOut,

			f"voltageOut{scanchannel}mean" : voltagesOutMean,
			f"voltageOut{scanchannel}std" : voltagesOutStd
		}

		np.savez(f"channel{scanchannel}.", **data)

		ax[1].errorbar(voltagesIn, voltagesOutMean, voltagesOutStd)

		ax[0].set_xlabel("Voltage In [V]")
		ax[0].set_ylabel("Voltage Out [V]")
		ax[0].set_title("Measurements")
		ax[0].grid()

		ax[1].set_xlabel("Voltage In [V]")
		ax[1].set_ylabel("Voltage Out [V]")
		ax[1].set_title("Average")
		ax[1].grid()

		plt.savefig(f"channel{scanchannel}.png")
		plt.savefig(f"channel{scanchannel}.svg")
		plt.show()