def process(self, out=None):
IM = self.get_input()
pad = False
if len(IM.shape) == 2:
#for 2D cases
pad = True
data_temp = numpy.expand_dims(IM.as_array(), axis=0)
else:
data_temp = IM.as_array()
sinogram_id, arr_out = astra.create_sino3d_gpu(data_temp,
self.proj_geom,
self.vol_geom)
astra.data3d.delete(sinogram_id)
if pad is True:
arr_out = numpy.squeeze(arr_out, axis=0)
if out is None:
out = AcquisitionData(arr_out,
deep_copy=False,
geometry=self.sinogram_geometry.copy(),
suppress_warning=True)
return out
else:
out.fill(arr_out)
def process(self, out=None):
IM = self.get_input()
sinogram_id, arr_out = astra.create_sino(IM.as_array(), self.proj_id)
astra.data2d.delete(sinogram_id)
if out is None:
out = AcquisitionData(arr_out,
deep_copy=False,
geometry=self.sinogram_geometry.copy(),
suppress_warning=True)
return out
else:
out.fill(arr_out)
def direct(self, x, out=None):
if self.tigre_geom.is2D:
data_temp = np.expand_dims(x.as_array(),axis=0)
arr_out = Ax.Ax(data_temp, self.tigre_geom, self.tigre_angles, projection_type=self.method['direct'])
arr_out = np.squeeze(arr_out, axis=1)
else:
arr_out = Ax.Ax(x.as_array(), self.tigre_geom, self.tigre_angles, projection_type=self.method['direct'])
if out is None:
out = AcquisitionData(arr_out, deep_copy=False, geometry=self._range_geometry.copy(), suppress_warning=True)
return out
else:
out.fill(arr_out)
def process(self, out=None):
IM = self.get_input()
pad = False
if len(IM.shape) == 2:
#for 2D cases
pad = True
data_temp = np.expand_dims(IM.as_array(), axis=0)
else:
data_temp = IM.as_array()
if out is None:
sinogram_id, arr_out = astra.create_sino3d_gpu(
data_temp, self.proj_geom, self.vol_geom)
else:
if pad:
arr_out = np.expand_dims(out.as_array(), axis=0)
else:
arr_out = out.as_array()
sinogram_id = astra.data3d.link('-sino', self.proj_geom, arr_out)
self.create_backprojection3d_gpu(data_temp, self.proj_geom,
self.vol_geom, False, sinogram_id)
#clear the memory on GPU
astra.data3d.delete(sinogram_id)
if pad is True:
arr_out = np.squeeze(arr_out, axis=0)
if out is None:
out = AcquisitionData(arr_out,
deep_copy=False,
geometry=self.sinogram_geometry.copy(),
suppress_warning=True)
return out
else:
out.fill(arr_out)
def direct(self, x, out=None):
data = x.as_array()
if self.tigre_geom.is2D:
data_temp = np.expand_dims(data, axis=0)
arr_out = self.__call_Ax(data_temp)
arr_out = np.squeeze(arr_out, axis=1)
else:
arr_out = self.__call_Ax(data)
#if single angle projection remove the dimension for CIL
if arr_out.shape[0] == 1:
arr_out = np.squeeze(arr_out, axis=0)
if out is None:
out = AcquisitionData(arr_out,
deep_copy=False,
geometry=self._range_geometry.copy(),
suppress_warning=True)
return out
else:
out.fill(arr_out)