diff options
Diffstat (limited to 'samples')
| -rw-r--r-- | samples/python/s009_projection_matrix.py | 2 | ||||
| -rw-r--r-- | samples/python/s015_fp_bp.py | 6 | ||||
| -rw-r--r-- | samples/python/s017_OpTomo.py | 2 |
3 files changed, 5 insertions, 5 deletions
diff --git a/samples/python/s009_projection_matrix.py b/samples/python/s009_projection_matrix.py index c4c4557..e20d58c 100644 --- a/samples/python/s009_projection_matrix.py +++ b/samples/python/s009_projection_matrix.py @@ -46,7 +46,7 @@ W = astra.matrix.get(matrix_id) # Manually use this projection matrix to do a projection: import scipy.io P = scipy.io.loadmat('phantom.mat')['phantom256'] -s = W.dot(P.flatten()) +s = W.dot(P.ravel()) s = np.reshape(s, (len(proj_geom['ProjectionAngles']),proj_geom['DetectorCount'])) import pylab diff --git a/samples/python/s015_fp_bp.py b/samples/python/s015_fp_bp.py index fa0bf86..ff0b30a 100644 --- a/samples/python/s015_fp_bp.py +++ b/samples/python/s015_fp_bp.py @@ -46,12 +46,12 @@ class astra_wrap(object): def matvec(self,v): sid, s = astra.create_sino(np.reshape(v,(vol_geom['GridRowCount'],vol_geom['GridColCount'])),self.proj_id) astra.data2d.delete(sid) - return s.flatten() + return s.ravel() def rmatvec(self,v): bid, b = astra.create_backprojection(np.reshape(v,(len(proj_geom['ProjectionAngles']),proj_geom['DetectorCount'],)),self.proj_id) astra.data2d.delete(bid) - return b.flatten() + return b.ravel() vol_geom = astra.create_vol_geom(256, 256) proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,180,False)) @@ -65,7 +65,7 @@ proj_id = astra.create_projector('cuda',proj_geom,vol_geom) sinogram_id, sinogram = astra.create_sino(P, proj_id) # Reshape the sinogram into a vector -b = sinogram.flatten() +b = sinogram.ravel() # Call lsqr with ASTRA FP and BP import scipy.sparse.linalg diff --git a/samples/python/s017_OpTomo.py b/samples/python/s017_OpTomo.py index 967fa64..214e9a7 100644 --- a/samples/python/s017_OpTomo.py +++ b/samples/python/s017_OpTomo.py @@ -50,7 +50,7 @@ pylab.figure(2) pylab.imshow(sinogram) # Run the lsqr linear solver -output = scipy.sparse.linalg.lsqr(W, sinogram.flatten(), iter_lim=150) +output = scipy.sparse.linalg.lsqr(W, sinogram.ravel(), iter_lim=150) rec = output[0].reshape([256, 256]) pylab.figure(3) |