[Scipy-svn] r3500 - in trunk/scipy/ndimage: . segment tests

scipy-svn@scip... scipy-svn@scip...
Wed Nov 7 12:31:19 CST 2007


Author: oliphant
Date: 2007-11-07 12:31:18 -0600 (Wed, 07 Nov 2007)
New Revision: 3500

Modified:
   trunk/scipy/ndimage/segment/Segmenter_EXT.c
   trunk/scipy/ndimage/segment/Segmenter_IMPL.c
   trunk/scipy/ndimage/segment/__init__.py
   trunk/scipy/ndimage/setup.py
   trunk/scipy/ndimage/tests/test_segmenter.py
Log:
Fix up segment code.

Modified: trunk/scipy/ndimage/segment/Segmenter_EXT.c
===================================================================
--- trunk/scipy/ndimage/segment/Segmenter_EXT.c	2007-11-07 17:53:37 UTC (rev 3499)
+++ trunk/scipy/ndimage/segment/Segmenter_EXT.c	2007-11-07 18:31:18 UTC (rev 3500)
@@ -386,7 +386,6 @@
     int type;
     int itype;
     int groups;
-    int mode;
     npy_intp *dims;
     double *fP1;
     unsigned short *fP2;
@@ -437,7 +436,7 @@
     {  NULL, NULL },
 };
 
-void init_segmenter()
+void init_segmenter(void)
 {
     Py_InitModule("_segmenter", NDI_SegmenterMethods);
     import_array();

Modified: trunk/scipy/ndimage/segment/Segmenter_IMPL.c
===================================================================
--- trunk/scipy/ndimage/segment/Segmenter_IMPL.c	2007-11-07 17:53:37 UTC (rev 3499)
+++ trunk/scipy/ndimage/segment/Segmenter_IMPL.c	2007-11-07 18:31:18 UTC (rev 3500)
@@ -1315,8 +1315,8 @@
 	unsigned short omask[11][11];
 	int olapValuesC[4];
 	int olapValuesO[4];
-	int CloseMaskSize;
-	int OpenMaskSize;
+	int CloseMaskSize=1;
+	int OpenMaskSize=1;
 	int LowValue1, HighValue1;   
 	int LowValue2, HighValue2;  
 	int spadSize;
@@ -2735,7 +2735,7 @@
 	float *colFilter;
 	float filterResult1;
 	float filterResult2;
-	float lawsLL;
+	float lawsLL=1.0;
 	float t;
 	float maxValue;
 	float scale;

Modified: trunk/scipy/ndimage/segment/__init__.py
===================================================================
--- trunk/scipy/ndimage/segment/__init__.py	2007-11-07 17:53:37 UTC (rev 3499)
+++ trunk/scipy/ndimage/segment/__init__.py	2007-11-07 18:31:18 UTC (rev 3500)
@@ -1,3 +1,5 @@
+# Segmentation package 
+# Author: Tom Waite, 2007
 
-ver = '0.0.1'
-
+from _segmenter import *
+from objectdata import *

Modified: trunk/scipy/ndimage/setup.py
===================================================================
--- trunk/scipy/ndimage/setup.py	2007-11-07 17:53:37 UTC (rev 3499)
+++ trunk/scipy/ndimage/setup.py	2007-11-07 18:31:18 UTC (rev 3500)
@@ -14,6 +14,7 @@
         include_dirs=['src']+[get_include()],
     )
 
+    config.add_subpackage('segment')
     config.add_data_dir('tests')
 
     return config

Modified: trunk/scipy/ndimage/tests/test_segmenter.py
===================================================================
--- trunk/scipy/ndimage/tests/test_segmenter.py	2007-11-07 17:53:37 UTC (rev 3499)
+++ trunk/scipy/ndimage/tests/test_segmenter.py	2007-11-07 18:31:18 UTC (rev 3500)
@@ -1,30 +1,27 @@
 
 import numpy as N
+from numpy.testing import *
 import scipy.ndimage.segment as S
 
+inputname = 'slice112.raw'
+
+import os
+filename = os.path.join(os.path.split(__file__)[0],inputname)
+
+
 def shen_castan(image, IIRFilter=0.8, scLow=0.3, window=7, lowThreshold=220+2048, highThreshold=600+2048, dust=16):
-	datatype = [('L', 'i', 1), ('R', 'i', 1), ('T', 'i', 1), ('B', 'i', 1),
-            	    ('Label', 'i', 1), ('Area', 'i', 1), ('cX', 'f', 1), ('cY', 'f', 1),
-            	    ('curveClose', 'i', 1), ('cXB', 'f', 1), ('cYB', 'f', 1), ('bLength', 'f', 1),
-            	    ('minRadius', 'f', 1), ('maxRadius', 'f', 1), ('aveRadius', 'f', 1), ('ratio', 'f', 1),
-            	    ('compactness', 'f', 1), ('voxelMean', 'f', 1), ('voxelVar', 'f', 1), ('TEM', 'f', 20)]
 	labeledEdges, numberObjects = S.shen_castan_edges(scLow, IIRFilter, window, lowThreshold, highThreshold, image)
 	# allocated struct array for edge object measures. for now just the rect bounding box
-	ROIList = N.zeros(numberObjects, dtype=datatype)
+	ROIList = N.zeros(numberObjects, dtype=S.objstruct)
 	# return the bounding box for each connected edge
 	S.get_object_stats(labeledEdges, ROIList)
 	return labeledEdges, ROIList[ROIList['Area']>dust]
 
 def sobel(image, sLow=0.3, tMode=1, lowThreshold=220+2048, highThreshold=600+2048, BPHigh=10.0, apearture=21, dust=16):
-	datatype = [('L', 'i', 1), ('R', 'i', 1), ('T', 'i', 1), ('B', 'i', 1),
-            	    ('Label', 'i', 1), ('Area', 'i', 1), ('cX', 'f', 1), ('cY', 'f', 1),
-            	    ('curveClose', 'i', 1), ('cXB', 'f', 1), ('cYB', 'f', 1), ('bLength', 'f', 1),
-            	    ('minRadius', 'f', 1), ('maxRadius', 'f', 1), ('aveRadius', 'f', 1), ('ratio', 'f', 1),
-            	    ('compactness', 'f', 1), ('voxelMean', 'f', 1), ('voxelVar', 'f', 1), ('TEM', 'f', 20)]
 	# get sobel edge points. return edges that are labeled (1..numberObjects)
 	labeledEdges, numberObjects = S.sobel_edges(sLow, tMode, lowThreshold, highThreshold, BPHigh, apearture, image)
 	# allocated struct array for edge object measures. for now just the rect bounding box
-	ROIList = N.zeros(numberObjects, dtype=datatype)
+	ROIList = N.zeros(numberObjects, dtype=S.objstruct)
 	# return the bounding box for each connected edge
 	S.get_object_stats(labeledEdges, ROIList)
 	# thin (medial axis transform) of the sobel edges as the sobel produces a 'band edge'
@@ -33,16 +30,11 @@
 
 def canny(image, cSigma=1.0, cLow=0.5, cHigh=0.8, tMode=1, lowThreshold=220+2048, highThreshold=600+2048,
           BPHigh=10.0, apearture=21, dust=16):
-	datatype = [('L', 'i', 1), ('R', 'i', 1), ('T', 'i', 1), ('B', 'i', 1),
-            	    ('Label', 'i', 1), ('Area', 'i', 1), ('cX', 'f', 1), ('cY', 'f', 1),
-            	    ('curveClose', 'i', 1), ('cXB', 'f', 1), ('cYB', 'f', 1), ('bLength', 'f', 1),
-            	    ('minRadius', 'f', 1), ('maxRadius', 'f', 1), ('aveRadius', 'f', 1), ('ratio', 'f', 1),
-            	    ('compactness', 'f', 1), ('voxelMean', 'f', 1), ('voxelVar', 'f', 1), ('TEM', 'f', 20)]
 	# get canny edge points. return edges that are labeled (1..numberObjects)
 	labeledEdges, numberObjects = S.canny_edges(cSigma, cLow, cHigh, tMode, lowThreshold, highThreshold, 
 			                           BPHigh, apearture, image)
 	# allocated struct array for edge object measures. for now just the rect bounding box
-	ROIList = N.zeros(numberObjects, dtype=datatype)
+	ROIList = N.zeros(numberObjects, dtype=S.objstruct)
 	# return the bounding box for each connected edge
 	S.get_object_stats(labeledEdges, ROIList)
 	return labeledEdges, ROIList[ROIList['Area']>dust]
@@ -73,7 +65,7 @@
 
 def segment_regions():
 	# get slice from the CT volume
-	image = get_slice('slice112.raw')
+	image = get_slice(filename)
 	# need a copy of original image as filtering will occur on the extracted slice
     	sourceImage = image.copy()
 	# Sobel is the first level segmenter. Sobel magnitude and MAT (medial axis transform)
@@ -89,7 +81,7 @@
 
 def grow_regions():
 	# get slice from the CT volume
-	image = get_slice('slice112.raw')
+	image = get_slice(filename)
 	regionMask, numberRegions = region_grow(image)
 	return regionMask, numberRegions 
 
@@ -128,34 +120,23 @@
         slice.tofile(filename)
 
 
-# test 1
-def test1():
-    import Segmenter as S
-    image = S.get_slice('slice112.raw')
-    sourceImage = image.copy()
-    edges, objects = S.sobel(image)
-    S.get_shape_mask(edges, objects)
-    S.get_voxel_measures(sourceImage, edges, objects)
-    S.get_texture_measures(sourceImage, edges, objects)
-
-# test 2
-def test2():
-    import volumeInput as V
-    import Segmenter as S
-    sourceImage, labeledMask, ROIList = S.segment_regions()
-
-
-# test 3
-def test3():
-    import Segmenter as S
-    regionMask, numberRegions = S.grow_regions()
-    regionMask.max()
-    S.save_slice(regionMask, 'regionMask.raw')
-
-
-
 class TestSegmenter(NumpyTestCase):
     def test_1(self):
+	image = get_slice(filename)
+	sourceImage = image.copy()
+	edges, objects = sobel(image)
+	get_shape_mask(edges, objects)
+	get_voxel_measures(sourceImage, edges, objects)
+	get_texture_measures(sourceImage, edges, objects)
 
+    def test_2(self):
+	sourceImage, labeledMask, ROIList = segment_regions()
 
+    def test_3(self):
+	regionMask, numberRegions = grow_regions()
+	regionMask.max()
+	#save_slice(regionMask, 'regionMask.raw')
+
     
+if __name__ == "__main__":
+    NumpyTest().run()



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