

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
np.mean([1.003, 1.004, 1.004])









    Out[4]:





1.0036666666666665



In [5]:

    
key = '7.25cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.0037,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.011, 1.011],
    depth=13
)

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









    



Cutout factor = 1.007 | 0.7%
Inverse factor = 0.993 | -0.7%



In [6]:

    
key = '8.3cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.0037,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.006, ],
    depth=13
)

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









    



Cutout factor = 1.002 | 0.2%
Inverse factor = 0.998 | -0.2%



In [7]:

    
key = '9.5cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.0037,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.009],
    depth=13
)

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









    



Cutout factor = 1.005 | 0.5%
Inverse factor = 0.995 | -0.5%



In [8]:

    
# Standard insert 10app 6MeV
np.mean([1.004])









    Out[8]:





1.004



In [9]:

    
key = '8.3cm_repoured_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.004,
    energy=6
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.010, 1.010],
    depth=13
)

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









    



Cutout factor = 1.006 | 0.6%
Inverse factor = 0.994 | -0.6%



In [ ]: