In [1]:

    

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

from electronfactors import (
    new_reading, calc_and_display)


    

In [2]:

    

data = dict()


    

In [3]:

    

# Standard insert
np.mean([1.033, 1.033])


    

    
Out[3]:





1.0329999999999999

In [4]:

    

key = 'concave_cutout'

data[key] = dict()

data[key]['depth'] = []
data[key]['ionisation'] = []
data[key]['reference'] = 1.033
data[key]['energy'] = 12

data = new_reading(
    key=key, data=data,
    ionisation=[1.007, 1.006, 1.006],
    depth=25    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.009, 1.009],
    depth=24   
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.011, 1.011],
    depth=23 
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.013],
    depth=22
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.013],
    depth=21
)

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


    

    













    




Cutout factor = 0.975 | -2.5%
Inverse factor = 1.026 | 2.6%

In [5]:

    

key = 'concave_ellipse'
data[key] = dict()
data[key]['depth'] = []
data[key]['ionisation'] = []
data[key]['reference'] = 1.033
data[key]['energy'] = 12

data = new_reading(
    key=key, data=data,
    ionisation=[1.001, 1.001],
    depth=25    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.004, 1.004],
    depth=24    
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.008, 1.007, 1.007],
    depth=23   
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.009, 1.009],
    depth=22   
)

data = new_reading(
    key=key, data=data,
    ionisation=[1.009],
    depth=21   
)

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


    

    













    




Cutout factor = 0.971 | -2.9%
Inverse factor = 1.030 | 3.0%

In [6]:

    

# Standard insert
np.mean([1.033, 1.033])


    

    
Out[6]:





1.0329999999999999