Analyse and fit Coulomb peaks

Load packages

import os
import numpy as np
import qcodes
from qcodes.plots.qcmatplotlib import MatPlot
import matplotlib.pyplot as plt
%matplotlib inline

import qtt
import qtt.algorithms.coulomb
from qtt.algorithms.coulomb import analyseCoulombPeaks
from qtt.data import load_example_dataset

dataset=load_example_dataset('coulomb_peak')
qtt.data.plot_dataset(dataset)

Fit Coulomb peaks

peaks=qtt.algorithms.coulomb.analyseCoulombPeaks(dataset, fig=10)
_=plt.plot(peaks[0]['xbottom'], peaks[0]['ybottoml'], '+y', markersize=25)

fitCoulombPeaks: peak 0: position -36.25 max 2583.48 valid 1
filterPeaks: 1 -> 1 good peaks
peakScores: noise factor 1.00
peakScores: 0: height 1225.8 halfwidth 9.0, score 1287.70

peaks[0]

{'p': 348,
 'x': -36.2474,
 'y': 2583.48,
 'gaussfit': array([-3.57655832e+01,  1.22339747e+01,  7.86964941e+04]),
 'halfvaluelow': 1857.8959,
 'height': 1451.1682,
 'valid': 1,
 'lowvalue': 1132.3118,
 'type': 'peak',
 'phalf0': 294,
 'phalfl': None,
 'xhalfl': -45.286672018348625,
 'xfoot': -53.90643419525066,
 'yhalfl': 1860.27,
 'pbottomlow': 223,
 'pbottom': 255,
 'pbottoml': 255,
 'xbottom': -51.9487,
 'xbottoml': -51.9487,
 'vbottom': 1357.64,
 'ybottoml': 1357.64,
 'score': 1287.6962930290897,
 'slope': 101.20512200893356,
 'heightscore': 0.8574826172722056,
 'scorerelative': 0.9007514745793096,
 'noisefactor': 0.9998830914752265}