diff options
| -rw-r--r-- | Wrappers/Python/ccpi/astra/astra_processors.py | 140 |
1 files changed, 29 insertions, 111 deletions
diff --git a/Wrappers/Python/ccpi/astra/astra_processors.py b/Wrappers/Python/ccpi/astra/astra_processors.py index 8cc0df4..94a8745 100644 --- a/Wrappers/Python/ccpi/astra/astra_processors.py +++ b/Wrappers/Python/ccpi/astra/astra_processors.py @@ -46,7 +46,8 @@ class AstraForwardProjector(DataSetProcessor): NotImplemented def checkInput(self, dataset): - if dataset.number_of_dimensions == 3 or dataset.number_of_dimensions == 2: + if dataset.number_of_dimensions == 3 or\ + dataset.number_of_dimensions == 2: return True else: raise ValueError("Expected input dimensions is 2 or 3, got {0}"\ @@ -63,9 +64,14 @@ class AstraForwardProjector(DataSetProcessor): def process(self): IM = self.getInput() - sinogram_id, DATA = astra.create_sino(IM.as_array(), self.proj_id) + DATA = SinogramData(geometry=self.sinogram_geometry) + #sinogram_id, DATA = astra.create_sino( IM.as_array(), + # self.proj_id) + sinogram_id, DATA.array = astra.create_sino(IM.as_array(), + self.proj_id) astra.data2d.delete(sinogram_id) - return SinogramData(DATA,geometry=self.sinogram_geometry) + #return SinogramData(array=DATA, geometry=self.sinogram_geometry) + return DATA class AstraBackProjector(DataSetProcessor): '''AstraBackProjector @@ -126,12 +132,14 @@ class AstraBackProjector(DataSetProcessor): def process(self): DATA = self.getInput() - rec_id, IM = astra.create_backprojection(DATA.as_array(), self.proj_id) + IM = VolumeData(geometry=self.volume_geometry) + rec_id, IM.array = astra.create_backprojection(DATA.as_array(), + self.proj_id) astra.data2d.delete(rec_id) - return VolumeData(IM,geometry=self.volume_geometry) + return IM -class AstraForwardProjectorMC(DataSetProcessor): - '''AstraForwardProjector +class AstraForwardProjectorMC(AstraForwardProjector): + '''AstraForwardProjector Multi channel Forward project VolumeDataSet to SinogramDataSet using ASTRA proj_id. @@ -139,72 +147,27 @@ class AstraForwardProjectorMC(DataSetProcessor): Parameter: proj_id Output: SinogramDataSet ''' - - def __init__(self, - volume_geometry=None, - sinogram_geometry=None, - proj_id=None, - device='cpu'): - kwargs = { - 'volume_geometry' : volume_geometry, - 'sinogram_geometry' : sinogram_geometry, - 'proj_id' : proj_id, - 'device' : device - } - - #DataSetProcessor.__init__(self, **kwargs) - super(AstraForwardProjectorMC, self).__init__(**kwargs) - - self.setVolumeGeometry(volume_geometry) - self.setSinogramGeometry(sinogram_geometry) - - # Set up ASTRA Volume and projection geometry, not to be stored in self - vol_geom, proj_geom = convert_geometry_to_astra(self.volume_geometry, - self.sinogram_geometry) - - # ASTRA projector, to be stored - if device == 'cpu': - # Note that 'line' is only for parallel (2D) and only one option - self.setProjector(astra.create_projector('line', proj_geom, vol_geom) ) - elif device == 'gpu': - self.setProjector(astra.create_projector('cuda', proj_geom, vol_geom) ) - else: - NotImplemented - def checkInput(self, dataset): - if dataset.number_of_dimensions == 3 or dataset.number_of_dimensions == 2: + if dataset.number_of_dimensions == 2 or \ + dataset.number_of_dimensions == 3 or \ + dataset.number_of_dimensions == 4: return True else: - return True - #raise ValueError("Expected input dimensions is 2 or 3, got {0}"\ - # .format(dataset.number_of_dimensions)) - - def setProjector(self, proj_id): - self.proj_id = proj_id - - def setVolumeGeometry(self, volume_geometry): - self.volume_geometry = volume_geometry - - def setSinogramGeometry(self, sinogram_geometry): - self.sinogram_geometry = sinogram_geometry - + raise ValueError("Expected input dimensions is 2 or 3, got {0}"\ + .format(dataset.number_of_dimensions)) def process(self): IM = self.getInput() #create the output Sinogram DATA = SinogramData(geometry=self.sinogram_geometry) - #DATA = numpy.zeros((self.sinogram_geometry.angles.size, - # self.sinogram_geometry.pixel_num_h, - # 1, - # self.sinogram_geometry.channels), - # 'float32') + for k in range(DATA.geometry.channels): sinogram_id, DATA.as_array()[k] = astra.create_sino(IM.as_array()[k], self.proj_id) astra.data2d.delete(sinogram_id) return DATA -class AstraBackProjectorMC(DataSetProcessor): - '''AstraBackProjector +class AstraBackProjectorMC(AstraBackProjector): + '''AstraBackProjector Multi channel Back project SinogramDataSet to VolumeDataSet using ASTRA proj_id. @@ -212,62 +175,17 @@ class AstraBackProjectorMC(DataSetProcessor): Parameter: proj_id Output: VolumeDataSet ''' - - def __init__(self, - volume_geometry=None, - sinogram_geometry=None, - proj_id=None, - device='cpu'): - kwargs = { - 'volume_geometry' : volume_geometry, - 'sinogram_geometry' : sinogram_geometry, - 'proj_id' : proj_id, - 'device' : device - } - - #DataSetProcessor.__init__(self, **kwargs) - super(AstraBackProjectorMC, self).__init__(**kwargs) - - self.setVolumeGeometry(volume_geometry) - self.setSinogramGeometry(sinogram_geometry) - - # Set up ASTRA Volume and projection geometry, not to be stored in self - vol_geom, proj_geom = convert_geometry_to_astra(self.volume_geometry, - self.sinogram_geometry) - - # ASTRA projector, to be stored - if device == 'cpu': - # Note that 'line' is only for parallel (2D) and only one option - self.setProjector(astra.create_projector('line', proj_geom, vol_geom) ) - elif device == 'gpu': - self.setProjector(astra.create_projector('cuda', proj_geom, vol_geom) ) - else: - NotImplemented - def checkInput(self, dataset): - if dataset.number_of_dimensions == 3 or dataset.number_of_dimensions == 2: + if dataset.number_of_dimensions == 2 or \ + dataset.number_of_dimensions == 3 or \ + dataset.number_of_dimensions == 4: return True else: - return True - #raise ValueError("Expected input dimensions is 2 or 3, got {0}"\ - # .format(dataset.number_of_dimensions)) - - def setProjector(self, proj_id): - self.proj_id = proj_id - - def setVolumeGeometry(self, volume_geometry): - self.volume_geometry = volume_geometry - - def setSinogramGeometry(self, sinogram_geometry): - self.sinogram_geometry = sinogram_geometry - + raise ValueError("Expected input dimensions is 2 or 3, got {0}"\ + .format(dataset.number_of_dimensions)) def process(self): DATA = self.getInput() - #IM = numpy.zeros((self.volume_geometry.voxel_num_x, - # self.volume_geometry.voxel_num_y, - # 1, - # self.volume_geometry.channels), - # 'float32') + IM = VolumeData(geometry=self.volume_geometry) for k in range(IM.geometry.channels): |