In [1]:
%pylab inline
from scipy.interpolate import interp1d
from IPython.display import Image
Below are the recorded measurements for the first batch of cutout factor measurements
The following cell is used to initialise the ionisation to dose conversion function. Data is extracted from table 20 within TRS398. R50 of the 12 MeV beam is $4.75~g/cm^2$
In [2]:
zOnR50 = concatenate((array([0.02]), arange(0.05,1.25,0.05)))
R50of45 = array([0.997,1,1.004,1.008,1.012,1.017,1.021,1.026,1.03,
1.035,1.04,1.045,1.051,1.056,1.062,1.067,1.073,1.08,
1.086,1.092,1.099,1.106,1.113,1.120,1.128])
R50of50 = array([0.991,0.994,0.998,1.002,1.006,1.011,1.016,1.02,1.025,
1.03,1.035,1.041,1.046,1.052,1.058,1.064,1.07,1.076,
1.083,1.09,1.097,1.104,1.112,1.119,1.128])
R50of47_5 = mean([R50of45,R50of50],axis=0)
stopRatio = interp1d(zOnR50 * 47.5,R50of47_5)
These measurements were done on Harry 2694, with a Markus chamber set to +300 V. The sensitivity was $1.398 \times 10^9$. All measurements were done at 100 SSD with a 12 MeV beam and a $10\times10$ cm applicator. Below are the readings recorded in chronological order.
In [3]:
standard_insert_reading = {}
cutout_reading = {}
factor = {}
In [4]:
standard_insert_reading = array([])
standard_insert_reading = append(standard_insert_reading,mean([1.533,1.533,1.533])) # Measured before
standard_insert_reading = append(standard_insert_reading,mean([1.532,1.531,1.532])) # Measured after
standard_insert_reading = mean(standard_insert_reading)
In [5]:
def outputFunction(cutout,depth,readings):
if size(readings) == 1:
cutout_reading = readings
else:
stop_ratio_corrected = stopRatio(depth) * readings
scatter(depth,stop_ratio_corrected)
ylabel('Stopping power ratio corrected')
xlabel('Depth (mm)')
title('Relative ionsation to relative dose')
show()
cutout_reading = readings[argmax(stop_ratio_corrected)]
print("Reading = %0.3f" %(cutout_reading))
factor = standard_insert_reading / cutout_reading
print("Cutout factor = %0.3f | %0.1f%%" %(factor, (factor - 1) * 100))
return cutout_reading, factor
In [6]:
cutout = '043'
cutout_reading[cutout] = mean([1.521,1.520]) # ionisation at depth 25 mm RW3
# cutout_reading[cutout] = mean([1.445,]) # ionisation at depth 24 mm RW3
factor[cutout] = standard_insert_reading / cutout_reading[cutout]
print("Cutout factor = %0.3f | %0.1f%%" %(factor[cutout], (factor[cutout] - 1) * 100))
Image('../figures/saved/'+cutout+'.png')
Out[6]:
In [7]:
cutout = '106'
cutout_reading[cutout] = mean([1.531,1.531,1.531]) # ionisation at depth 25 mm RW3
factor[cutout] = standard_insert_reading / cutout_reading[cutout]
print("Cutout factor = %0.3f | %0.1f%%" %(factor[cutout], (factor[cutout] - 1) * 100))
Image('../figures/saved/'+cutout+'.png')
Out[7]:
In [8]:
cutout = '058'
cutout_reading[cutout] = mean([1.518,1.519,1.519]) # ionisation at depth 25 mm RW3
factor[cutout] = standard_insert_reading / cutout_reading[cutout]
print("Cutout factor = %0.3f | %0.1f%%" %(factor[cutout], (factor[cutout] - 1) * 100))
Image('../figures/saved/'+cutout+'.png')
Out[8]:
In [9]:
cutout = '033'
cutout_reading[cutout] = mean([1.522,1.522,1.522]) # ionisation at depth 25 mm RW3
factor[cutout] = standard_insert_reading / cutout_reading[cutout]
print("Cutout factor = %0.3f | %0.1f%%" %(factor[cutout], (factor[cutout] - 1) * 100))
Image('../figures/saved/'+cutout+'.png')
Out[9]:
In [10]:
cutout = '019'
cutout_reading[cutout] = mean([1.530,1.531,1.531]) # ionisation at depth 25 mm RW3
factor[cutout] = standard_insert_reading / cutout_reading[cutout]
print("Cutout factor = %0.3f | %0.1f%%" %(factor[cutout], (factor[cutout] - 1) * 100))
Image('../figures/saved/'+cutout+'.png')
Out[10]:
In [11]:
cutout = '083'
depth = array([25,24,23,22])
readings = array([])
readings = append(readings,mean([1.516,1.517,1.516])) # ionisation at depth 25 mm RW3
readings = append(readings,mean([1.519,1.519])) # ionisation at depth 24 mm RW3
readings = append(readings,mean([1.522])) # ionisation at depth 23 mm RW3
readings = append(readings,mean([1.520])) # ionisation at depth 22 mm RW3
cutout_reading[cutout], factor[cutout] = outputFunction(cutout,depth,readings)
Image('../figures/saved/'+cutout+'.png')
Out[11]:
In [12]:
with open('cutout_factors','r') as f:
loaded_factors = eval(f.read())
factors_to_save = dict(list(loaded_factors.items()) + list(factor.items()))
with open('cutout_factors','w') as f:
f.write(str(factors_to_save))