Merge pull request tomopy#305 from decarlof/master

added filter choice in write_center
dgursoy · Dec 8, 2017 · 4b1c34d · 4b1c34d
2 parents 058e5ce + 8e28b3d
commit 4b1c34d
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Showing 2 changed files with 65 additions and 4 deletions.
diff --git a/test/test_recon/test_rotation.py b/test/test_recon/test_rotation.py
@@ -72,7 +72,8 @@ def test_write_center(self):
         write_center(
             read_file('proj.npy'),
             read_file('angle.npy'),
-            dpath, cen_range=cen_range)
+            dpath, cen_range=cen_range,
+            algorithm='gridrec', filter_name='shepp')
         for m in range(cen.size):
             assert_equals(
                 os.path.isfile(

diff --git a/tomopy/recon/rotation.py b/tomopy/recon/rotation.py
@@ -191,7 +191,8 @@ def _find_center_cost(
     center = np.array(center, dtype='float32')
     rec = recon(
         tomo_ind, theta, center,
-        sinogram_order=sinogram_order, algorithm='gridrec')
+        sinogram_order=sinogram_order, 
+        algorithm='gridrec')
 
     if mask is True:
         rec = circ_mask(rec, axis=0)
@@ -386,7 +387,7 @@ def find_center_pc(proj1, proj2, tol=0.5):
 
 def write_center(
         tomo, theta, dpath='tmp/center', cen_range=None, ind=None,
-        mask=False, ratio=1., sinogram_order=False):
+        mask=False, ratio=1., sinogram_order=False, algorithm='gridrec', filter_name='parzen'):
     """
     Save images reconstructed with a range of rotation centers.
 
@@ -416,6 +417,64 @@ def write_center(
     sinogram_order: bool, optional
         Determins whether data is a stack of sinograms (True, y-axis first axis)
         or a stack of radiographs (False, theta first axis).
+    algorithm : {str, function}
+        One of the following string values.
+
+        'art'
+            Algebraic reconstruction technique :cite:`Kak:98`.
+        'bart'
+            Block algebraic reconstruction technique.
+        'fbp'
+            Filtered back-projection algorithm.
+        'gridrec'
+            Fourier grid reconstruction algorithm :cite:`Dowd:99`,
+            :cite:`Rivers:06`.
+        'mlem'
+            Maximum-likelihood expectation maximization algorithm
+            :cite:`Dempster:77`.
+        'osem'
+            Ordered-subset expectation maximization algorithm
+            :cite:`Hudson:94`.
+        'ospml_hybrid'
+            Ordered-subset penalized maximum likelihood algorithm with
+            weighted linear and quadratic penalties.
+        'ospml_quad'
+            Ordered-subset penalized maximum likelihood algorithm with
+            quadratic penalties.
+        'pml_hybrid'
+            Penalized maximum likelihood algorithm with weighted linear
+            and quadratic penalties :cite:`Chang:04`.
+        'pml_quad'
+            Penalized maximum likelihood algorithm with quadratic penalty.
+        'sirt'
+            Simultaneous algebraic reconstruction technique.
+    filter_name : str, optional
+        Name of the filter for analytic reconstruction.
+
+        'none'
+            No filter.
+        'shepp'
+            Shepp-Logan filter (default).
+        'cosine'
+            Cosine filter.
+        'hann'
+            Cosine filter.
+        'hamming'
+            Hamming filter.
+        'ramlak'
+            Ram-Lak filter.
+        'parzen'
+            Parzen filter.
+        'butterworth'
+            Butterworth filter.
+        'custom'
+            A numpy array of size `next_power_of_2(num_detector_columns)/2`
+            specifying a custom filter in Fourier domain. The first element
+            of the filter should be the zero-frequency component.
+        'custom2d'
+            A numpy array of size `num_projections*next_power_of_2(num_detector_columns)/2`
+            specifying a custom angle-dependent filter in Fourier domain. The first element
+            of each filter should be the zero-frequency component.
     """
     tomo = dtype.as_float32(tomo)
     theta = dtype.as_float32(theta)
@@ -444,7 +503,8 @@ def write_center(
                 theta,
                 center=center,
                 sinogram_order=True,
-                algorithm='gridrec',
+                algorithm=algorithm,
+                filter_name=filter_name,
                 nchunk=1)
 
     # Apply circular mask.