forked from dcollins4096/star_formation_at_nif
-
Notifications
You must be signed in to change notification settings - Fork 0
/
trim_and_align.py
34 lines (28 loc) · 1.27 KB
/
trim_and_align.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
from starter2 import *
import regions.regions_coarse as regions_coarse
import regions.regions_align as regions_align
reload(regions_align)
reload(regions_coarse)
#Coarse Cut from raw radiograph
#the import will extract the two frames from the raw radiograph.
#
# Produces the following images:
# <frame>_full_images, the full tiff for <frame>
# <frame>_noises, used to find the noise floor for extraction
# <frame>_rough, the rough cut for each shot (by hand)
# <frame>_trim, trim the image to the noise floor
trim_fname='data/trim.h5'
if not os.path.exists(trim_fname):
trimmed = regions_coarse.do_coarse_trim()
regions_coarse.save_trim(trimmed,trim_fname)
else:
trimmed = regions_coarse.read(trim_fname)
# Align the two shots to the point on the second fiducial.
# Produces:
# <shot>_align1, the horizontal cuts through the fiducial. Mostly a development tool
# <frame>_trim_align, only the trimmed and aligned image
aligned_fname = 'data/aligned.h5'
if not os.path.exists(aligned_fname) or True:
#regions_align.align_regions(trimmed, aligned_fname)
#regions_align.align_regions2(trimmed, align_fname=aligned_fname, shot_list=['s120'])
regions_align.align_regions2(trimmed, align_fname=aligned_fname, shot_list=['r0','r60','r120','s90','s120'])