

In [14]:

    
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 [15]:

    
data = dict()

6 MeV



In [16]:

    
energy_to_reference_depth(6)









    Out[16]:





array([13])



In [17]:

    
# Standard insert 10app 6MeV
np.mean([1.016, 1.016])









    Out[17]:





1.016



In [18]:

    
key = '9.5cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.016,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.021, 1.021],
    depth=13    
)

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









    



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



In [19]:

    
key = '7.25cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.016,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.023, 1.023],
    depth=13    
)

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









    



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



In [20]:

    
key = '8.5x10.9cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.016,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.019, 1.019],
    depth=13    
)

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









    



Cutout factor = 1.003 | 0.3%
Inverse factor = 0.997 | -0.3%



In [21]:

    
# Standard insert 10app 6MeV
np.mean([1.016])









    Out[21]:





1.016



In [22]:

    
key = '6.7x12cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.016,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.027, 1.026, 1.026],
    depth=13    
)

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









    



Cutout factor = 1.010 | 1.0%
Inverse factor = 0.990 | -1.0%



In [23]:

    
key = '5.3x12.5cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.015,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.011, 1.012, 1.011],
    depth=13    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.007],
    depth=12    
)

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









    












    



Cutout factor = 0.996 | -0.4%
Inverse factor = 1.004 | 0.4%



In [24]:

    
key = '5x5cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.014,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[0.9912, 0.9908],
    depth=13    
)

data = new_reading(
    key=key, data=data,
    ionisation=[0.9884],
    depth=12   
)

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









    












    



Cutout factor = 0.977 | -2.3%
Inverse factor = 1.023 | 2.3%



In [25]:

    
key = '4x5cm_6MeV'

data = initialise(
    key=key, data=data,
    reference=1.014,
    energy=6    
)

data = new_reading(
    key=key, data=data,
    ionisation=[0.9756],
    depth=13    
)

# data = new_reading(
#     key=key, data=data,
#     ionisation=[0.9756],
#     depth=13    
# )

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









    



Cutout factor = 0.962 | -3.8%
Inverse factor = 1.039 | 3.9%



In [26]:

    
# Standard insert 10app 6MeV
np.mean([1.014, 1.015, 1.014])









    Out[26]:





1.0143333333333333



In [ ]: