Fix error caused by bad revert

MATLAB/Source/Siddon_projection.cu

@@ -246,7 +246,8 @@ int siddon_ray_projection(float const * const img, Geometry geo, float** result,
 
     // Prepare for MultiGPU
     int deviceCount = 0;
-    gpuErrchk(cudaGetDeviceCount(&deviceCount));
+    cudaGetDeviceCount(&deviceCount);
+    cudaCheckErrors("Error checking devices");
     if (deviceCount == 0) {
         mexErrMsgIdAndTxt("Ax:Siddon_projection:GPUselect","There are no available device(s) that support CUDA\n");
     }
@@ -381,7 +382,7 @@ int siddon_ray_projection(float const * const img, Geometry geo, float** result,
     cudaDeviceReset();
     return 0;
 }
-void CreateTexture(int num_devices, float* imagedata,Geo geo, cudaTextureObject_t *texImage)
+void CreateTexture(int num_devices, float* imagedata,Geometry geo, cudaTextureObject_t *texImage)
 {
     size_t size_image=geo.nVoxelX*geo.nVoxelY*geo.nVoxelZ;
     for (unsigned int i = 0; i < num_devices; i++){
@@ -402,7 +403,7 @@ void CreateTexture(int num_devices, float* imagedata,Geo geo, cudaTextureObject_
         copyParams.extent   = make_cudaExtent(geo.nVoxelX,geo.nVoxelY,geo.nVoxelZ);
         copyParams.kind     = cudaMemcpyHostToDevice;
         cudaMemcpy3D(&copyParams);
-        checkCudaErrors("Texture memory data copy fail");
+        cudaCheckErrors("Texture memory data copy fail");
         //Array creation End
 
         cudaResourceDesc    texRes;
@@ -418,7 +419,7 @@ void CreateTexture(int num_devices, float* imagedata,Geo geo, cudaTextureObject_
         texDescr.addressMode[2] = cudaAddressModeBorder;
         texDescr.readMode = cudaReadModeElementType;
         cudaCreateTextureObject(&texImage[i], &texRes, &texDescr, NULL);
-        checkCudaErrors("Texture object creation fail");
+        cudaCheckErrors("Texture object creation fail");
     }
 }
 

Python/purge.sh

@@ -1,6 +1,6 @@
-#!/bin/bash
-
-rm -r build dist tigre.egg-info .idea 
-rm _Ax.so _Atb.so _tvdenoising.so _minTV.so _AwminTV.so
-rm tigre/Source/_Ax.cpp tigre/Source/_Atb.cpp tigre/Source/_tvdenoising.cpp tigre/Source/_minTV.cpp tigre/Source/_AwminTV.cpp
+#!/bin/bash
+
+rm -r build dist tigre.egg-info .idea 
+rm _Ax.so _Atb.so _tvdenoising.so _minTV.so _AwminTV.so
+rm tigre/Source/_Ax.cpp tigre/Source/_Atb.cpp tigre/Source/_tvdenoising.cpp tigre/Source/_minTV.cpp tigre/Source/_AwminTV.cpp
 pip uninstall tigre

Python/tests/ipnbdoctest.py

@@ -1,36 +1,36 @@
-import os
-import subprocess
-import tempfile
-
-import nbformat
-
-
-def _notebook_run(path):
-    """Execute a notebook via nbconvert and collect output.
-       :returns (parsed nb object, execution errors)
-    """
-    dirname, __ = os.path.split(path)
-    os.chdir(dirname)
-    with tempfile.NamedTemporaryFile(suffix=".ipynb") as fout:
-        args = ["nbconvert", "--to", "notebook", "--execute",
-                "--ExecutePreprocessor.timeout=60",
-                "--output", fout.name, path]
-        subprocess.check_call(args)
-
-        fout.seek(0)
-        nb = nbformat.read(fout, nbformat.current_nbformat)
-
-    errors = [output for cell in nb.cells if "outputs" in cell
-              for output in cell["outputs"] \
-              if output.output_type == "error"]
-
-    return nb, errors
-
-
-def test_ipynb():
-    nb, errors = _notebook_run('../tigre/demos/d01_create_geometry.ipynb')
-    assert errors == []
-
-
-if __name__ == '__main__':
-    test_ipynb()
+import os
+import subprocess
+import tempfile
+
+import nbformat
+
+
+def _notebook_run(path):
+    """Execute a notebook via nbconvert and collect output.
+       :returns (parsed nb object, execution errors)
+    """
+    dirname, __ = os.path.split(path)
+    os.chdir(dirname)
+    with tempfile.NamedTemporaryFile(suffix=".ipynb") as fout:
+        args = ["nbconvert", "--to", "notebook", "--execute",
+                "--ExecutePreprocessor.timeout=60",
+                "--output", fout.name, path]
+        subprocess.check_call(args)
+
+        fout.seek(0)
+        nb = nbformat.read(fout, nbformat.current_nbformat)
+
+    errors = [output for cell in nb.cells if "outputs" in cell
+              for output in cell["outputs"] \
+              if output.output_type == "error"]
+
+    return nb, errors
+
+
+def test_ipynb():
+    nb, errors = _notebook_run('../tigre/demos/d01_create_geometry.ipynb')
+    assert errors == []
+
+
+if __name__ == '__main__':
+    test_ipynb()

Python/tests/test_algorithms.py

@@ -1,49 +1,49 @@
-from __future__ import division
-import unittest
-import tigre
-from tigre.utilities.Ax import Ax
-import numpy as np
-from tigre.algorithms.iterative_recon_alg import IterativeReconAlg
-import tigre.algorithms as algs
-class AlgorithmsTestCase(unittest.TestCase):
-
-    def setUp(self):
-        geo = tigre.geometry()
-        geo.DSD = 1536
-        geo.DSO = 1000
-        geo.nDetector = np.array((128, 127))
-        geo.dDetector = np.array((0.8, 0.8)) * 4.
-        geo.sDetector = geo.nDetector * geo.dDetector
-        geo.nVoxel = np.array((63, 62, 61))
-        geo.sVoxel = np.array((256, 256, 256))
-        geo.dVoxel = geo.sVoxel / geo.nVoxel
-        geo.offOrigin = np.array((0, 0, 0))
-        geo.offDetector = np.array((0, 0))
-        geo.accuracy = 0.5
-        geo.mode = 'cone'
-        self.angles = np.linspace(0, 2 * np.pi, 100, dtype=np.float32)
-        self.geo = geo
-        self.img = np.ones((63, 62, 61), dtype=np.float32)
-        self.proj = Ax(self.img,self.geo,self.angles)
-        self.niter=2
-    def test_mainiter_itrecalg(self):
-        alg = IterativeReconAlg(self.proj,self.geo,self.angles,self.niter,**dict(verbose=False))
-        self.assertIsNone(alg.run_main_iter())
-
-    def test_shape_sart(self):
-        self.assertTupleEqual(tigre.algorithms.sart(self.proj,self.geo,self.angles,niter=1).shape,
-                              tuple(self.geo.nVoxel))
-    def test_shape_sirt(self):
-        self.assertTupleEqual(tigre.algorithms.sirt(self.proj,self.geo,self.angles,niter=1).shape,
-                              tuple(self.geo.nVoxel))
-    def test_shape_ossart(self):
-        self.assertTupleEqual(tigre.algorithms.sirt(self.proj,self.geo,self.angles,niter=1).shape,
-                              tuple(self.geo.nVoxel))
-    def test_shape_asdpocs(self):
-        self.assertTupleEqual(algs.asd_pocs(self.proj,self.geo,self.angles,niter=1).shape,
-                              tuple(self.geo.nVoxel))
-    def test_shape_awasdpocs(self):
-        self.assertTupleEqual(algs.awasd_pocs(self.proj,self.geo,self.angles,niter=1).shape,
-                              tuple(self.geo.nVoxel))
-if __name__=='__main__':
+from __future__ import division
+import unittest
+import tigre
+from tigre.utilities.Ax import Ax
+import numpy as np
+from tigre.algorithms.iterative_recon_alg import IterativeReconAlg
+import tigre.algorithms as algs
+class AlgorithmsTestCase(unittest.TestCase):
+
+    def setUp(self):
+        geo = tigre.geometry()
+        geo.DSD = 1536
+        geo.DSO = 1000
+        geo.nDetector = np.array((128, 127))
+        geo.dDetector = np.array((0.8, 0.8)) * 4.
+        geo.sDetector = geo.nDetector * geo.dDetector
+        geo.nVoxel = np.array((63, 62, 61))
+        geo.sVoxel = np.array((256, 256, 256))
+        geo.dVoxel = geo.sVoxel / geo.nVoxel
+        geo.offOrigin = np.array((0, 0, 0))
+        geo.offDetector = np.array((0, 0))
+        geo.accuracy = 0.5
+        geo.mode = 'cone'
+        self.angles = np.linspace(0, 2 * np.pi, 100, dtype=np.float32)
+        self.geo = geo
+        self.img = np.ones((63, 62, 61), dtype=np.float32)
+        self.proj = Ax(self.img,self.geo,self.angles)
+        self.niter=2
+    def test_mainiter_itrecalg(self):
+        alg = IterativeReconAlg(self.proj,self.geo,self.angles,self.niter,**dict(verbose=False))
+        self.assertIsNone(alg.run_main_iter())
+
+    def test_shape_sart(self):
+        self.assertTupleEqual(tigre.algorithms.sart(self.proj,self.geo,self.angles,niter=1).shape,
+                              tuple(self.geo.nVoxel))
+    def test_shape_sirt(self):
+        self.assertTupleEqual(tigre.algorithms.sirt(self.proj,self.geo,self.angles,niter=1).shape,
+                              tuple(self.geo.nVoxel))
+    def test_shape_ossart(self):
+        self.assertTupleEqual(tigre.algorithms.sirt(self.proj,self.geo,self.angles,niter=1).shape,
+                              tuple(self.geo.nVoxel))
+    def test_shape_asdpocs(self):
+        self.assertTupleEqual(algs.asd_pocs(self.proj,self.geo,self.angles,niter=1).shape,
+                              tuple(self.geo.nVoxel))
+    def test_shape_awasdpocs(self):
+        self.assertTupleEqual(algs.awasd_pocs(self.proj,self.geo,self.angles,niter=1).shape,
+                              tuple(self.geo.nVoxel))
+if __name__=='__main__':
         unittest.main()

Python/tests/test_projections.py

@@ -1,82 +1,82 @@
-import unittest
-from tigre.utilities.geometry import geometry
-from tigre.utilities.Ax import Ax
-from tigre.utilities.Atb import Atb
-import numpy as np
-
-class ProjectionTestCase(unittest.TestCase):
-
-    def setUp(self):
-        geo = geometry()
-        geo.DSD = 1536
-        geo.DSO = 1000
-        geo.nDetector = np.array((128, 127))
-        geo.dDetector = np.array((0.8, 0.8)) * 4
-        geo.sDetector = geo.nDetector * geo.dDetector
-        geo.nVoxel = np.array((63, 62, 61))
-        geo.sVoxel = np.array((256, 256, 256))
-        geo.dVoxel = geo.sVoxel / geo.nVoxel
-        geo.offOrigin = np.array((0, 0, 0))
-        geo.offDetector = np.array((0, 0))
-        geo.accuracy = 0.5
-        geo.mode = 'cone'
-        self.angles = np.linspace(0, 2 * np.pi, 100, dtype=np.float32)
-        self.geo = geo
-        self.img = np.ones((63, 62, 61), dtype=np.float32)
-        self.proj = Ax(self.img,self.geo,self.angles)
-    def test_geo(self):
-        self.assertIsNone(self.geo.check_geo(self.angles))
-
-    def test_proj_interpolated_shape(self):
-        img = self.img
-        self.assertTupleEqual(Ax(img,self.geo,self.angles,'interpolated').shape,(100,128,127))
-
-    def test_proj_ray_voxel_shape(self):
-        self.assertTupleEqual(Ax(self.img,self.geo,self.angles,'ray-voxel').shape,(100,128,127))
-
-    def test_proj_parallel_interpolated_shape(self):
-        setattr(self.geo,'mode','parallel')
-        self.assertTupleEqual(Ax(self.img,self.geo,self.angles,'interpolated').shape,(100,128,127))
-
-    def test_proj_parallel_ray_voxel_shape(self):
-        setattr(self.geo,'mode','parallel')
-        self.assertTupleEqual(Ax(self.img,self.geo,self.angles,'ray-voxel').shape,(100,128,127))
-
-    def test_backproj_matched_cone_shape(self):
-        setattr(self.geo,'mode','cone')
-        self.assertTupleEqual(Atb(self.proj,self.geo,self.angles,'matched').shape,(63,62,61))
-
-    def test_backproj_FDK_cone_shape(self):
-        setattr(self.geo,'mode','cone')
-        self.assertTupleEqual(Atb(self.proj, self.geo, self.angles, 'FDK').shape, (63, 62, 61))
-
-    def test_backproj_parallel_shape(self):
-        setattr(self.geo,'mode','parallel')
-        self.assertTupleEqual(Atb(self.proj, self.geo, self.angles,'matched').shape, (63, 62, 61))
-
-    def test_backproj_matched_cone_spherical_shape(self):
-        setattr(self.geo,'mode','cone')
-        angles_1 = self.angles
-        angles_2 = np.ones((len(angles_1)),dtype=np.float32)*np.array([np.pi/4],dtype=np.float32)
-        angles_3 = np.zeros((len(angles_1)),dtype=np.float32)
-        new_angles = np.vstack((angles_1,angles_2,angles_3)).T
-        self.assertTupleEqual(Atb(self.proj, self.geo, new_angles,'matched').shape, (63, 62, 61))
-
-    def test_backproj_FDK_cone_spherical_shape(self):
-        setattr(self.geo,'mode','cone')
-        angles_1 = self.angles
-        angles_2 = np.ones((len(angles_1)), dtype=np.float32) * np.array([np.pi / 4], dtype=np.float32)
-        angles_3 = np.zeros((len(angles_1)), dtype=np.float32)
-        new_angles = np.vstack((angles_1, angles_2, angles_3)).T
-        self.assertTupleEqual(Atb(self.proj, self.geo, new_angles,'FDK').shape, (63, 62, 61))
-
-    def test_backproj_parallel_spherical_shape(self):
-        setattr(self.geo,'mode','parallel')
-        angles_1 = self.angles
-        angles_2 = np.ones((len(angles_1)), dtype=np.float32) * np.array([np.pi / 4], dtype=np.float32)
-        angles_3 = np.zeros((len(angles_1)), dtype=np.float32)
-        new_angles = np.vstack((angles_1, angles_2, angles_3)).T
-        self.assertTupleEqual(Atb(self.proj, self.geo, new_angles).shape, (63, 62, 61))
-
-if __name__=='__main__':
-        unittest.main()
+import unittest
+from tigre.utilities.geometry import geometry
+from tigre.utilities.Ax import Ax
+from tigre.utilities.Atb import Atb
+import numpy as np
+
+class ProjectionTestCase(unittest.TestCase):
+
+    def setUp(self):
+        geo = geometry()
+        geo.DSD = 1536
+        geo.DSO = 1000
+        geo.nDetector = np.array((128, 127))
+        geo.dDetector = np.array((0.8, 0.8)) * 4
+        geo.sDetector = geo.nDetector * geo.dDetector
+        geo.nVoxel = np.array((63, 62, 61))
+        geo.sVoxel = np.array((256, 256, 256))
+        geo.dVoxel = geo.sVoxel / geo.nVoxel
+        geo.offOrigin = np.array((0, 0, 0))
+        geo.offDetector = np.array((0, 0))
+        geo.accuracy = 0.5
+        geo.mode = 'cone'
+        self.angles = np.linspace(0, 2 * np.pi, 100, dtype=np.float32)
+        self.geo = geo
+        self.img = np.ones((63, 62, 61), dtype=np.float32)
+        self.proj = Ax(self.img,self.geo,self.angles)
+    def test_geo(self):
+        self.assertIsNone(self.geo.check_geo(self.angles))
+
+    def test_proj_interpolated_shape(self):
+        img = self.img
+        self.assertTupleEqual(Ax(img,self.geo,self.angles,'interpolated').shape,(100,128,127))
+
+    def test_proj_ray_voxel_shape(self):
+        self.assertTupleEqual(Ax(self.img,self.geo,self.angles,'ray-voxel').shape,(100,128,127))
+
+    def test_proj_parallel_interpolated_shape(self):
+        setattr(self.geo,'mode','parallel')
+        self.assertTupleEqual(Ax(self.img,self.geo,self.angles,'interpolated').shape,(100,128,127))
+
+    def test_proj_parallel_ray_voxel_shape(self):
+        setattr(self.geo,'mode','parallel')
+        self.assertTupleEqual(Ax(self.img,self.geo,self.angles,'ray-voxel').shape,(100,128,127))
+
+    def test_backproj_matched_cone_shape(self):
+        setattr(self.geo,'mode','cone')
+        self.assertTupleEqual(Atb(self.proj,self.geo,self.angles,'matched').shape,(63,62,61))
+
+    def test_backproj_FDK_cone_shape(self):
+        setattr(self.geo,'mode','cone')
+        self.assertTupleEqual(Atb(self.proj, self.geo, self.angles, 'FDK').shape, (63, 62, 61))
+
+    def test_backproj_parallel_shape(self):
+        setattr(self.geo,'mode','parallel')
+        self.assertTupleEqual(Atb(self.proj, self.geo, self.angles,'matched').shape, (63, 62, 61))
+
+    def test_backproj_matched_cone_spherical_shape(self):
+        setattr(self.geo,'mode','cone')
+        angles_1 = self.angles
+        angles_2 = np.ones((len(angles_1)),dtype=np.float32)*np.array([np.pi/4],dtype=np.float32)
+        angles_3 = np.zeros((len(angles_1)),dtype=np.float32)
+        new_angles = np.vstack((angles_1,angles_2,angles_3)).T
+        self.assertTupleEqual(Atb(self.proj, self.geo, new_angles,'matched').shape, (63, 62, 61))
+
+    def test_backproj_FDK_cone_spherical_shape(self):
+        setattr(self.geo,'mode','cone')
+        angles_1 = self.angles
+        angles_2 = np.ones((len(angles_1)), dtype=np.float32) * np.array([np.pi / 4], dtype=np.float32)
+        angles_3 = np.zeros((len(angles_1)), dtype=np.float32)
+        new_angles = np.vstack((angles_1, angles_2, angles_3)).T
+        self.assertTupleEqual(Atb(self.proj, self.geo, new_angles,'FDK').shape, (63, 62, 61))
+
+    def test_backproj_parallel_spherical_shape(self):
+        setattr(self.geo,'mode','parallel')
+        angles_1 = self.angles
+        angles_2 = np.ones((len(angles_1)), dtype=np.float32) * np.array([np.pi / 4], dtype=np.float32)
+        angles_3 = np.zeros((len(angles_1)), dtype=np.float32)
+        new_angles = np.vstack((angles_1, angles_2, angles_3)).T
+        self.assertTupleEqual(Atb(self.proj, self.geo, new_angles).shape, (63, 62, 61))
+
+if __name__=='__main__':
+        unittest.main()