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CTRecon
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pub
CTRecon
Commits
1ed4bb8c
Commit
1ed4bb8c
authored
Nov 05, 2018
by
Will Langford
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adding gridrec.py
parent
8591b731
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.gitignore
.gitignore
+1
-0
README.md
README.md
+2
-0
gridrec.py
gridrec.py
+82
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images/coil_tomopy_recon.gif
images/coil_tomopy_recon.gif
+0
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.gitignore
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1ed4bb8c
_data/
\ No newline at end of file
README.md
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...
...
@@ -2,6 +2,8 @@
## Tomopy

### Gridrec
*
parallel beam
...
...
gridrec.py
0 → 100644
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1ed4bb8c
# coding: utf-8
# ## Gridrec
#
# Here is an example on how to use [TomoPy](http://tomopy.readthedocs.io/en/latest/) with the gridrec algorithm.
#
# [user manual](https://media.readthedocs.org/pdf/tomopy/latest/tomopy.pdf)
# In[3]:
# get_ipython().run_line_magic('pylab', 'inline')
# In[4]:
import
tomopy
import
dxchange
import
numpy
as
np
import
matplotlib.pyplot
as
plt
import
ipyvolume
as
ipv
if
__name__
==
'__main__'
:
haveLoaded
=
False
if
(
haveLoaded
):
print
(
"loading projection data..."
)
proj
=
np
.
load
(
"projection_data.npy"
)
else
:
print
(
"loading angle data..."
)
ctdata
=
np
.
loadtxt
(
"test_scan_250/_ctdata.txt"
,
skiprows
=
3
)
theta
=
np
.
deg2rad
(
ctdata
[:,
1
])
fname
=
'_data/test_scan_250/test scan 250_0001.tif'
print
(
"loading tiff stack..."
)
indices
=
[
i
for
i
in
range
(
1
,
752
)]
data
=
dxchange
.
read_tiff_stack
(
fname
,
indices
)
print
(
np
.
shape
(
data
))
# downsample and minus log
print
(
"downsampling and taking minus log..."
)
proj
=
tomopy
.
minus_log
(
data
[::
1
,::
8
,::
8
])
print
(
np
.
shape
(
proj
))
print
(
"saving projection data..."
)
np
.
save
(
'projection_data'
,
proj
)
rot_center
=
proj
.
shape
[
2
]
/
2
# gridrec
print
(
"running reconstruction..."
)
rec
=
tomopy
.
recon
(
proj
,
theta
,
sinogram_order
=
False
,
center
=
rot_center
,
algorithm
=
'art'
)
# LPrec (not working)
# rec = tomopy.recon(proj, theta, center=rot_center,
# algorithm=tomopy.lprec, lpmethod='lpfbp',
# filter_name='parzen')
# ASTRA (not working)
options
=
{
'proj_type'
:
'linear'
,
'method'
:
'FBP'
}
rec
=
tomopy
.
recon
(
proj
,
theta
,
center
=
rot_center
,
algorithm
=
tomopy
.
astra
,
options
=
options
)
print
(
"applying circular mask..."
)
rec
=
tomopy
.
circ_mask
(
rec
,
axis
=
0
,
ratio
=
0.75
)
print
(
"saving data to reconstruction_data.npy..."
)
np
.
save
(
'reconstruction_data'
,
rec
)
# use jupyter notebook to visualize results
# print("visualizing...")
# ipv.figure()
# vol = ipv.volshow(rec)
# ipv.show()
images/coil_tomopy_recon.gif
0 → 100644
View file @
1ed4bb8c
6.8 MB
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