Merge pull request #1 from effigies/release_v1

Version 1.0 release

Author: effigies

LICENSE

@@ -0,0 +1,21 @@
+Copyright (c) 2011, Nakeisha Schimke. All rights reserved.
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of the The University of Tulsa nor the names of its
+   contributors may be used to endorse or promote products derived from this
+   software without specific prior written permission.
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
+ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

quickshear.py

@@ -1,103 +1,83 @@
 #!/usr/bin/python
-"""
-Copyright (c) 2011, Nakeisha Schimke. All rights reserved.
-Redistribution and use in source and binary forms, with or without 
-modification, are permitted provided that the following conditions are met:
- * Redistributions of source code must retain the above copyright notice, this    
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice, 
-   this list of conditions and the following disclaimer in the documentation    
-   and/or other materials provided with the distribution.
- * Neither the name of the The University of Tulsa nor the names of its 
-   contributors may be used to endorse or promote products derived from this 
-   software without specific prior written permission.
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND 
-ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 
-WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 
-DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
-ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 
-(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 
-LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
-ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 
-(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 
-SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-"""
 import numpy
 import nibabel as nb
 import sys
 import logging
 
+
 def edge_mask(mask):
     """Create an edge of brain mask from a binary brain mask.
-    
+
     Return a two-dimensional edge of brain mask.
     """
     brain = numpy.zeros(mask.shape[1:])
     # iterate over axial
-    for i in range(0,mask.shape[1]-1):
+    for i in range(0, mask.shape[1] - 1):
         # iterate over coronal
-        for k in range(mask.shape[2]-1,0,-1):
-            brain[i,k] = mask[:,i,k].any()
-	
-    edgemask = numpy.zeros(brain.shape,dtype='uint8')
-    for u in range(1,brain.shape[0]-2):
-        for v in range(1,brain.shape[1]-2):
-            if brain[u,v] + brain[u-1,v] == 1:
-	            edgemask[u,v] = 1
-            elif brain[u,v] + brain[u,v-1] == 1:
-	            edgemask[u,v] = 1
-            elif brain[u,v] + brain[u+1,v] == 1:
-	            edgemask[u,v] = 1
-            elif brain[u,v] + brain[u,v+1] == 1:
-	            edgemask[u,v] = 1
+        for k in range(mask.shape[2] - 1, 0, -1):
+            brain[i, k] = mask[:, i, k].any()
+
+    edgemask = numpy.zeros(brain.shape, dtype='uint8')
+    for u in range(1, brain.shape[0] - 2):
+        for v in range(1, brain.shape[1] - 2):
+            if brain[u, v] + brain[u - 1, v] == 1:
+                edgemask[u, v] = 1
+            elif brain[u, v] + brain[u, v - 1] == 1:
+                edgemask[u, v] = 1
+            elif brain[u, v] + brain[u + 1, v] == 1:
+                edgemask[u, v] = 1
+            elif brain[u, v] + brain[u, v + 1] == 1:
+                edgemask[u, v] = 1
     return edgemask
 
+
 def convex_hull(brain):
-    """Use Andrew's monotone chain algorithm to find the lower half of the convex hull.
-    
+    """Use Andrew's monotone chain algorithm to find the lower half of the
+    convex hull.
+
     Return a two-dimensional convex hull.
     """
     # convert brain to a list of points
     nz = numpy.nonzero(brain)
     # transpose so we get an n x 2 matrix where n_i = (x,y)
-    pts = numpy.array([nz[0],nz[1]]).transpose()
-    pts_t = pts.transpose()
-    
-    def cross(o,a,b):
-        return (a[0] - o[0])*(b[1]-o[1]) - (a[1] - o[1]) * (b[0] - o[0])
-    
+    pts = numpy.array([nz[0], nz[1]]).transpose()
+
+    def cross(o, a, b):
+        return (a[0] - o[0]) * (b[1] - o[1]) - (a[1] - o[1]) * (b[0] - o[0])
+
     lower = []
-    for i in range(0,pts.shape[0]):
-        p = (pts[i,0],pts[i,1])
-        while len(lower) >= 2 and cross(lower[-2],lower[-1],p) <= 0:
+    for i in range(0, pts.shape[0]):
+        p = (pts[i, 0], pts[i, 1])
+        while len(lower) >= 2 and cross(lower[-2], lower[-1], p) <= 0:
             lower.pop()
         lower.append(p)
 
     return numpy.array(lower).transpose()
-    
+
 
 def deface(anat_filename, mask_filename, defaced_filename, buff=10):
     """Deface neuroimage using a binary brain mask.
-    
+
     Keyword arguments:
     anat_filename -- the filename of the neuroimage to deface
     mask_filename -- the filename of the binary brain mask
     defaced_filename -- the filename of the defaced output image
-    buff -- the buffer size between the shearing line and the brain (default value is 10.0)
+    buff -- the buffer size between the shearing line and the brain
+        (default value is 10.0)
     """
     nii_anat = nb.load(anat_filename)
     nii_mask = nb.load(mask_filename)
-        
+
     if numpy.equal(nii_anat.shape, nii_mask.shape).all():
         pass
     else:
-        logger.WARNING("Anatomical and mask images do not have the same dimensions.")
+        logger.warning(
+            "Anatomical and mask images do not have the same dimensions.")
         sys.exit(-1)
 
     anat_ax = nb.orientations.aff2axcodes(nii_anat.get_affine())
     mask_ax = nb.orientations.aff2axcodes(nii_mask.get_affine())
 
-
     logger.debug("Anat image axes: {0}".format(anat_ax))
     logger.debug("Mask image axes: {0}".format(mask_ax))
     logger.debug("Mask shape!: {0}".format(nii_mask.shape))
@@ -109,7 +89,8 @@ def deface(anat_filename, mask_filename, defaced_filename, buff=10):
 
     if anat_ax[0] != mask_ax[0]:
         # align mask to anat space
-        logger.debug("Aligning mask to anatomical space... {0} -> {1}".format(mask_ax[0],anat_ax[0]))
+        logger.debug("Aligning mask to anatomical space... {0} -> {1}".format(
+            mask_ax[0], anat_ax[0]))
         mask = nb.orientations.flip_axis(mask, 0)
     if anat_ax[1] != 'P':
         # flip anatspace
@@ -130,55 +111,54 @@ def deface(anat_filename, mask_filename, defaced_filename, buff=10):
         logger.debug("Aligning mask to +y -> S")
         mask = nb.orientations.flip_axis(mask, 2)
 
-
     edgemask = edge_mask(mask)
     low = convex_hull(edgemask)
-    slope = (low[1][0]-low[1][1]) / (low[0][0]-low[0][1])
+    slope = (low[1][0] - low[1][1]) / (low[0][0] - low[0][1])
 
-    yint = low[1][0]-(low[0][0]*slope) - buff
-    ys = numpy.arange(0,mask.shape[2])*slope + yint
-    defaced_mask = numpy.ones(mask.shape,dtype='uint8')
+    yint = low[1][0] - (low[0][0] * slope) - buff
+    ys = numpy.arange(0, mask.shape[2]) * slope + yint
+    defaced_mask = numpy.ones(mask.shape, dtype='uint8')
 
-    for x in range(0, ys.size-1):
+    for x in range(0, ys.size - 1):
         if ys[x] < 0:
             break
         else:
-            ymax = min(ys[x],mask.shape[2])
-            defaced_mask[:,x,:ymax] = 0
-            
-    defaced_img = defaced_mask*anat    
-    
-    
-    if(anat_flip[1]):
-        newimg = nb.orientations.flip_axis(defaced_img, 1)
-    if(anat_flip[2]):
-        newimg = nb.orientations.flip_axis(defaced_img, 2)
-    else:
-        newimg = defaced_img
-    new_anat = nb.Nifti1Image(newimg,nii_anat.get_affine())
-    nb.save(new_anat,defaced_filename)
+            ymax = min(ys[x], mask.shape[2])
+            defaced_mask[:, x, :ymax] = 0
+
+    defaced_img = defaced_mask * anat
+
+    newimg = defaced_img
+    if anat_flip[1]:
+        newimg = nb.orientations.flip_axis(newimg, 1)
+    if anat_flip[2]:
+        newimg = nb.orientations.flip_axis(newimg, 2)
+    new_anat = nb.Nifti1Image(newimg, nii_anat.affine, nii_anat.header.copy())
+    nb.save(new_anat, defaced_filename)
     logger.info("Defaced file: {0}".format(defaced_filename))
 
+
 if __name__ == '__main__':
 
     logger = logging.getLogger(__name__)
-    #logging.basicConfig(filename="hull.log",level=logging.DEBUG)
+    # logging.basicConfig(filename="hull.log",level=logging.DEBUG)
     logger.setLevel(logging.DEBUG)
     ch = logging.StreamHandler()
     ch.setLevel(logging.DEBUG)
     logger.addHandler(ch)
 
     if len(sys.argv) < 4:
-        logger.debug("Usage: quickshear.py anat_file strip_file defaced_file [buffer]")
+        logger.debug(
+            "Usage: quickshear.py anat_file strip_file defaced_file [buffer]")
         sys.exit(-1)
     else:
         anatfile = sys.argv[1]
         stripfile = sys.argv[2]
         newfile = sys.argv[3]
         if len(sys.argv) >= 5:
             try:
-                buff = sys.argv[4]
+                buff = int(sys.argv[4])
             except:
-                raise NumberError
+                raise ValueError
             deface(anatfile, stripfile, newfile, buff)
         deface(anatfile, stripfile, newfile)