

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()

18 MeV



In [3]:

    
energy_to_reference_depth(18)









    Out[3]:





array([30])



In [4]:

    
# Standard insert 10app 18MeV 100MU
np.mean([1.095, 1.096])









    Out[4]:





1.0954999999999999



In [5]:

    
key = 'P13'

data = initialise(
    key=key, data=data,
    reference=1.096,
    energy=18
)

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.092, 1.093]),
    depth=30
)

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









    



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



In [6]:

    
# Standard insert 10app 18MeV 100MU
np.mean([1.096, 1.097])









    Out[6]:





1.0965

15 MeV



In [7]:

    
energy_to_reference_depth(15)









    Out[7]:





array([27])



In [8]:

    
# Standard insert 10app 15MeV 100MU
np.mean([1.076, 1.078])









    Out[8]:





1.077



In [9]:

    
# Standard insert 10app 15MeV 100MU
np.mean([1.076, 1.078])









    Out[9]:





1.077



In [10]:

    
key = '6.7x12cm_15MeV'

data = initialise(
    key=key, data=data,
    reference=1.077,
    energy=15
)

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.075, 1.076]),
    depth=27
)

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









    



Cutout factor = 0.999 | -0.1%
Inverse factor = 1.001 | 0.1%



In [11]:

    
# Standard insert 10app 15MeV 100MU
np.mean([1.076, 1.078])









    Out[11]:





1.077



In [12]:

    
key = '6.7x12cm_15MeV_old'

data = initialise(
    key=key, data=data,
    reference=1.077,
    energy=15
)

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.088, 1.089]),
    depth=27
)

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









    



Cutout factor = 1.011 | 1.1%
Inverse factor = 0.989 | -1.1%



In [13]:

    
# Standard insert 10app 15MeV 100MU
np.mean([1.077, 1.077])









    Out[13]:





1.077

6 MeV



In [14]:

    
energy_to_reference_depth(6)









    Out[14]:





array([13])



In [15]:

    
# Standard insert 10app 6MeV 100MU
np.mean([1.016, 1.016])









    Out[15]:





1.016



In [16]:

    
key = '6.7x12cm_6MeV'

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

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.014, 1.014]),
    depth=13
)

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









    



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



In [17]:

    
# Standard insert 10app 6MeV 100MU
np.mean([1.016, 1.015])









    Out[17]:





1.0154999999999998

9 MeV



In [18]:

    
energy_to_reference_depth(9)









    Out[18]:





array([20])



In [19]:

    
# Standard insert 10app 9MeV 100MU
np.mean([1.033, 1.033])









    Out[19]:





1.0329999999999999



In [20]:

    
key = '6.7x12cm_9MeV'

data = initialise(
    key=key, data=data,
    reference=1.033,
    energy=9
)

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.032, 1.033]),
    depth=20
)

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









    



Cutout factor = 1.000 | -0.0%
Inverse factor = 1.000 | 0.0%



In [21]:

    
# Standard insert 10app 9MeV 100MU
np.mean([1.033, 1.033])









    Out[21]:





1.0329999999999999



In [ ]:

18 MeV



In [22]:

    
energy_to_reference_depth(18)









    Out[22]:





array([30])



In [23]:

    
# Standard insert 10app 18MeV 100MU
np.mean([1.095, 1.097])









    Out[23]:





1.0960000000000001



In [24]:

    
key = '6.7x12cm_18MeV'

data = initialise(
    key=key, data=data,
    reference=1.096,
    energy=18
)

data = new_reading(
    key=key, data=data,
    ionisation=np.array([1.094, 1.096]),
    depth=30
)

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









    



Cutout factor = 0.999 | -0.1%
Inverse factor = 1.001 | 0.1%



In [25]:

    
# Standard insert 10app 18MeV 100MU
np.mean([1.096, 1.097])









    Out[25]:





1.0965



In [ ]: