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authorWillem Jan Palenstijn <Willem.Jan.Palenstijn@cwi.nl>2018-12-05 12:03:14 +0100
committerWillem Jan Palenstijn <Willem.Jan.Palenstijn@cwi.nl>2018-12-06 13:57:35 +0100
commit7bfc5b3713f750efe21992fcd8d02e840d5d4867 (patch)
tree4daeac31555bc6b568b5f8766cd27c90096d578e /samples
parente8be82070824fa370285142550c1e708561bd63d (diff)
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Read filter config for FBP from cfg.options
Since these settings are optional, they should have been in cfg.options instead of directly in cfg. The old syntax remains a fallback. This has the side-effect that the tomopy/astra interface can also supply them.
Diffstat (limited to 'samples')
-rw-r--r--samples/matlab/s014_FBP.m2
-rw-r--r--samples/matlab/s023_FBP_filters.m10
-rw-r--r--samples/python/s014_FBP.py2
-rw-r--r--samples/python/s023_FBP_filters.py11
4 files changed, 13 insertions, 12 deletions
diff --git a/samples/matlab/s014_FBP.m b/samples/matlab/s014_FBP.m
index 1fc6f90..038aa90 100644
--- a/samples/matlab/s014_FBP.m
+++ b/samples/matlab/s014_FBP.m
@@ -24,7 +24,7 @@ rec_id = astra_mex_data2d('create', '-vol', vol_geom);
cfg = astra_struct('FBP_CUDA');
cfg.ReconstructionDataId = rec_id;
cfg.ProjectionDataId = sinogram_id;
-cfg.FilterType = 'Ram-Lak';
+cfg.option.FilterType = 'Ram-Lak';
% possible values for FilterType:
% none, ram-lak, shepp-logan, cosine, hamming, hann, tukey, lanczos,
diff --git a/samples/matlab/s023_FBP_filters.m b/samples/matlab/s023_FBP_filters.m
index 4abec7e..d01b0d0 100644
--- a/samples/matlab/s023_FBP_filters.m
+++ b/samples/matlab/s023_FBP_filters.m
@@ -32,7 +32,7 @@ cfg.ProjectorId = proj_id;
% 1. Use a standard Ram-Lak filter
-cfg.FilterType = 'ram-lak';
+cfg.option.FilterType = 'ram-lak';
alg_id = astra_mex_algorithm('create', cfg);
astra_mex_algorithm('run', alg_id);
@@ -53,8 +53,8 @@ filter = kernel(1:halfFilterSize);
filter_geom = astra_create_proj_geom('parallel', 1.0, halfFilterSize, [0]);
filter_id = astra_mex_data2d('create', '-sino', filter_geom, filter);
-cfg.FilterType = 'projection';
-cfg.FilterSinogramId = filter_id;
+cfg.option.FilterType = 'projection';
+cfg.option.FilterSinogramId = filter_id;
alg_id = astra_mex_algorithm('create', cfg);
astra_mex_algorithm('run', alg_id);
@@ -77,8 +77,8 @@ kernel(floor(N/2)+1) = 0.5;
kernel_geom = astra_create_proj_geom('parallel', 1.0, N, [0]);
kernel_id = astra_mex_data2d('create', '-sino', kernel_geom, kernel);
-cfg.FilterType = 'rprojection';
-cfg.FilterSinogramId = kernel_id;
+cfg.option.FilterType = 'rprojection';
+cfg.option.FilterSinogramId = kernel_id;
alg_id = astra_mex_algorithm('create', cfg);
astra_mex_algorithm('run', alg_id);
diff --git a/samples/python/s014_FBP.py b/samples/python/s014_FBP.py
index f7cefd4..1c3a341 100644
--- a/samples/python/s014_FBP.py
+++ b/samples/python/s014_FBP.py
@@ -49,7 +49,7 @@ rec_id = astra.data2d.create('-vol', vol_geom)
cfg = astra.astra_dict('FBP_CUDA')
cfg['ReconstructionDataId'] = rec_id
cfg['ProjectionDataId'] = sinogram_id
-cfg['FilterType'] = 'Ram-Lak'
+cfg['option'] = { 'FilterType': 'Ram-Lak' }
# possible values for FilterType:
# none, ram-lak, shepp-logan, cosine, hamming, hann, tukey, lanczos,
diff --git a/samples/python/s023_FBP_filters.py b/samples/python/s023_FBP_filters.py
index 11518ac..a67c338 100644
--- a/samples/python/s023_FBP_filters.py
+++ b/samples/python/s023_FBP_filters.py
@@ -47,11 +47,12 @@ cfg = astra.astra_dict('FBP')
cfg['ReconstructionDataId'] = rec_id
cfg['ProjectionDataId'] = sinogram_id
cfg['ProjectorId'] = proj_id
+cfg['option'] = {}
# 1. Use a standard Ram-Lak filter
-cfg['FilterType'] = 'ram-lak'
+cfg['option']['FilterType'] = 'ram-lak'
alg_id = astra.algorithm.create(cfg)
astra.algorithm.run(alg_id)
@@ -71,8 +72,8 @@ filter = np.reshape(kernel[0:halfFilterSize], (1, halfFilterSize))
filter_geom = astra.create_proj_geom('parallel', 1.0, halfFilterSize, [0]);
filter_id = astra.data2d.create('-sino', filter_geom, filter);
-cfg['FilterType'] = 'projection'
-cfg['FilterSinogramId'] = filter_id
+cfg['option']['FilterType'] = 'projection'
+cfg['option']['FilterSinogramId'] = filter_id
alg_id = astra.algorithm.create(cfg)
astra.algorithm.run(alg_id)
rec_filter = astra.data2d.get(rec_id)
@@ -92,8 +93,8 @@ kernel[0, N//2] = 0.5
kernel_geom = astra.create_proj_geom('parallel', 1.0, N, [0]);
kernel_id = astra.data2d.create('-sino', kernel_geom, kernel);
-cfg['FilterType'] = 'rprojection'
-cfg['FilterSinogramId'] = kernel_id
+cfg['option']['FilterType'] = 'rprojection'
+cfg['option']['FilterSinogramId'] = kernel_id
alg_id = astra.algorithm.create(cfg)
astra.algorithm.run(alg_id)
rec_kernel = astra.data2d.get(rec_id)