diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/astra/optomo.py | 96 |
1 files changed, 66 insertions, 30 deletions
diff --git a/python/astra/optomo.py b/python/astra/optomo.py index 5a92998..dde719e 100644 --- a/python/astra/optomo.py +++ b/python/astra/optomo.py @@ -111,21 +111,7 @@ class OpTomo(scipy.sparse.linalg.LinearOperator): :param v: Volume to forward project. :type v: :class:`numpy.ndarray` """ - v = self.__checkArray(v, self.vshape) - vid = self.data_mod.link('-vol',self.vg,v) - s = np.zeros(self.sshape,dtype=np.float32) - sid = self.data_mod.link('-sino',self.pg,s) - - cfg = creators.astra_dict('FP'+self.appendString) - cfg['ProjectionDataId'] = sid - cfg['VolumeDataId'] = vid - cfg['ProjectorId'] = self.proj_id - fp_id = algorithm.create(cfg) - algorithm.run(fp_id) - - algorithm.delete(fp_id) - self.data_mod.delete([vid,sid]) - return s.ravel() + return self.FP(v, out=None).ravel() def rmatvec(self,s): """Implements the transpose operator. @@ -133,21 +119,7 @@ class OpTomo(scipy.sparse.linalg.LinearOperator): :param s: The projection data. :type s: :class:`numpy.ndarray` """ - s = self.__checkArray(s, self.sshape) - sid = self.data_mod.link('-sino',self.pg,s) - v = np.zeros(self.vshape,dtype=np.float32) - vid = self.data_mod.link('-vol',self.vg,v) - - cfg = creators.astra_dict('BP'+self.appendString) - cfg['ProjectionDataId'] = sid - cfg['ReconstructionDataId'] = vid - cfg['ProjectorId'] = self.proj_id - bp_id = algorithm.create(cfg) - algorithm.run(bp_id) - - algorithm.delete(bp_id) - self.data_mod.delete([vid,sid]) - return v.ravel() + return self.BP(s, out=None).ravel() def __mul__(self,v): """Provides easy forward operator by *. @@ -189,6 +161,70 @@ class OpTomo(scipy.sparse.linalg.LinearOperator): self.data_mod.delete([vid,sid]) return v + def FP(self,v,out=None): + """Perform forward projection. + + Output must have the right 2D/3D shape. Input may also be flattened. + + Output must also be contiguous and float32. This isn't required for the + input, but it is more efficient if it is. + + :param v: Volume to forward project. + :type v: :class:`numpy.ndarray` + :param out: Array to store result in. + :type out: :class:`numpy.ndarray` + """ + + v = self.__checkArray(v, self.vshape) + vid = self.data_mod.link('-vol',self.vg,v) + if out is None: + out = np.zeros(self.sshape,dtype=np.float32) + sid = self.data_mod.link('-sino',self.pg,out) + + cfg = creators.astra_dict('FP'+self.appendString) + cfg['ProjectionDataId'] = sid + cfg['VolumeDataId'] = vid + cfg['ProjectorId'] = self.proj_id + fp_id = algorithm.create(cfg) + algorithm.run(fp_id) + + algorithm.delete(fp_id) + self.data_mod.delete([vid,sid]) + return out + + def BP(self,s,out=None): + """Perform backprojection. + + Output must have the right 2D/3D shape. Input may also be flattened. + + Output must also be contiguous and float32. This isn't required for the + input, but it is more efficient if it is. + + :param : The projection data. + :type s: :class:`numpy.ndarray` + :param out: Array to store result in. + :type out: :class:`numpy.ndarray` + """ + s = self.__checkArray(s, self.sshape) + sid = self.data_mod.link('-sino',self.pg,s) + if out is None: + out = np.zeros(self.vshape,dtype=np.float32) + vid = self.data_mod.link('-vol',self.vg,out) + + cfg = creators.astra_dict('BP'+self.appendString) + cfg['ProjectionDataId'] = sid + cfg['ReconstructionDataId'] = vid + cfg['ProjectorId'] = self.proj_id + bp_id = algorithm.create(cfg) + algorithm.run(bp_id) + + algorithm.delete(bp_id) + self.data_mod.delete([vid,sid]) + return out + + + + class OpTomoTranspose(scipy.sparse.linalg.LinearOperator): """This object provides the transpose operation (``.T``) of the OpTomo object. |