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from cil.framework import DataProcessor, ImageData
import numpy as np
import gi
gi.require_version('Ufo','0.0')
from gi.repository import Ufo
class FBP_Stacked(DataProcessor):
def __init__(self, volume_geometry,
sinogram_geometry,
precision_mode='single',
stack_num=2):
kwargs = {
'volume_geometry': volume_geometry,
'sinogram_geometry': sinogram_geometry,
'precision_mode': precision_mode,
'stack_num': stack_num}
super(FBP_Stacked, self).__init__(**kwargs)
self.precision_mode = precision_mode
self.stack_num = stack_num
self.set_ImageGeometry(volume_geometry)
self.set_AcquisitionGeometry(sinogram_geometry)
def check_input(self, dataset):
if self.sinogram_geometry.dimension == '2D':
raise ValueError("Expected input dimensions is 3, got {0}" \
.format(dataset.number_of_dimensions))
return True
def set_ImageGeometry(self, volume_geometry):
self.volume_geometry = volume_geometry
def set_AcquisitionGeometry(self, sinogram_geometry):
self.sinogram_geometry = sinogram_geometry
def process(self, **kwargs):
# Get DATA
DATA = self.get_input()
DATA = DATA.as_array()
pm = Ufo.PluginManager()
graph = Ufo.TaskGraph()
scheduler = Ufo.Scheduler()
read = pm.get_task('memory-in')
read.props.pointer = DATA.__array_interface__['data'][0]
read.props.width = DATA.shape[1]
read.props.height = DATA.shape[0]
read.props.number = DATA.shape[2]
read.props.bitdepth = 32
fft = pm.get_task('fft')
fft.props.dimensions = 1
filter = pm.get_task('filter')
ifft = pm.get_task('ifft')
ifft.props.dimensions = 1
stack = pm.get_task('stack')
stack.props.number = self.stack_num
stacked_bp = pm.get_task('stacked-backproject')
stacked_bp.props.axis_pos = DATA.shape[1] / 2
stacked_bp.props.precision_mode = self.precision_mode
vol_arr = np.zeros(self.volume_geometry.shape, dtype=np.float32)
write = pm.get_task('memory-out')
write.props.pointer = vol_arr.__array_interface__['data'][0]
write.props.max_size = vol_arr.nbytes
graph.connect_nodes(read, fft)
graph.connect_nodes(fft, filter)
graph.connect_nodes(filter, ifft)
graph.connect_nodes(ifft, stack)
graph.connect_nodes(stack, stacked_bp)
graph.connect_nodes(stacked_bp, write)
scheduler.run(graph)
vol_arr = ImageData(vol_arr, deep_copy=False, geometry=self.volume_geometry.copy(), suppress_warning=True)
return vol_arr
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