

In [1]:

    
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

from electronfactors import (
    new_reading, calc_and_display, energy_to_reference_depth, 
    initialise)



In [2]:

    
data = dict()

6 MeV



In [3]:

    
energy_to_reference_depth(6)









    Out[3]:





array([13])



In [4]:

    
# Standard insert 10app 6MeV 150MU
np.mean([1.545, 1.547, 1.546, 1.546])









    Out[4]:





1.546



In [5]:

    
# Standard insert 6app 6MeV 150MU
np.mean([1.362, 1.361, 1.362])









    Out[5]:





1.3616666666666666



In [6]:

    
key = 'arbit'

data = initialise(
    key=key, data=data,
    reference=1.362,
    energy=6
)

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.333, 1.335, 1.332]),
    depth=13
) # point A

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.328]),
    depth=13
) # point B

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.336, 1.336]),
    depth=13
) # point C

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.331]),
    depth=12
) # point C

data[key]['factor'] = calc_and_display(**data[key])









    












    



Cutout factor = 0.981 | -1.9%
Inverse factor = 1.019 | 1.9%



In [7]:

    
# Standard insert 6app 6MeV 150MU
np.mean([1.361, 1.362, 1.360])









    Out[7]:





1.361



In [8]:

    
# Standard insert 10app 6MeV 150MU
np.mean([1.545])









    Out[8]:





1.5449999999999999



In [ ]: