-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathappend_results.py
executable file
·57 lines (36 loc) · 1.46 KB
/
append_results.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
# -*- coding: utf-8 -*-
"""
Append simulation results into one projection file per turn (i.e. sum up all separate simualations, but keep turns separated).
"""
import numpy as np
import os
#import matplotlib.pyplot as plt
for folder in ('70100644Phantom_labelled_no_bed',
'70114044Phantom_labelled_no_bed',
'70122044Phantom_labelled_no_bed',
'70135144Phantom_labelled_no_bed',
'70141544Phantom_labelled_no_bed',
'70153744Phantom_labelled_no_bed'):
path = os.path.join('/my/output/',folder)
phantomName = '/helical_proj_120kVSpectrum_' + folder + '_2000photons_per_Sim'
iter = 0
for turnNumber in range(0,23):
for number_of_simu in range(60):
print('Running sim no: %i, turn no: %i' %(number_of_simu, turnNumber))
myFile = (path + phantomName +
'_Sim_num_{}'.format(number_of_simu) +
'_Turn_num_{}'.format(turnNumber) +
'.npy')
if iter == 0: #turnNumber == 0:
projections = np.load(myFile)
else:
#None
projections = np.append(projections,np.load(myFile),axis = 0)
if number_of_simu > 0:
projectionsTot += projections
else:
projectionsTot = projections
saveName = path + '/HelicalSkullCT_' + folder +'_Dose150mGy_Turn_' + str(turnNumber) + '.data.npy'
print('Saving: %s' % saveName)
np.save(saveName,projectionsTot)
#plt.imshow(projections[1:-1:20,:,10])