analysis_ESR.py

# -*- coding: utf-8 -*-
"""
Created on Wed Jul  8 07:57:17 2020

Example of how to load the saturation curve

@author: Childresslab
"""



import spinmob as sm
import numpy as np


#d = sm.data.load(text='Select saturation curve ;)')


ds = sm.data.load_multiple(text='ESR data')

# Check the ckeys
print(ds[-1].ckeys)

# Get the axis names
label_s = []
for key in ds[-1].ckeys:
    label_s.append(key)

# Plot them
import matplotlib.pyplot as plt

plt.figure(tight_layout=True)

Z = [] # This will serve for a color plot
for d in ds:
    fs = d[0] # Frequency in GHz
    total_counts = d[1]# Total counts
    etotal_counts = np.sqrt(total_counts) # uncertainty in the count. Assuming poisson
    
    #Get the count rate in count/sec
    dt = d.headers['dt_on'] # count time in us
    rep = d.headers['repetition']
    nb_iter = d.headers['iteration']
    count_rate  = total_counts*1e6/(nb_iter*rep*dt) 
    ecount_rate = etotal_counts*1e6/(nb_iter*rep*dt) 
    
    # Estimate the contrast
    c = 100*(np.max(count_rate) - np.min(count_rate))/np.max(count_rate)
    txt = (d.path.split('/')[-1] + '\nPower %.2f dBm'%d.headers['Power']+
           '\n(Max-Min)/Max %.2f percent'%c)
    plt.errorbar(fs,count_rate*1e-3,yerr=ecount_rate*1e-3,
                 label =txt)
    
    # For the color plot
    Z.append(count_rate)

plt.legend()
plt.ylabel("Kcount/sec")
plt.xlabel(label_s[0])
plt.title(d.path, fontsize=9)


plt.figure(tight_layout=True)
plt.pcolor(Z)