# Copyright 2014 Diamond Light Source Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
.. module:: scikitimage_filter_back_projection
:platform: Unix
:synopsis: Wrapper for scikitimage FBP function
"""
import logging
from savu.plugins.reconstructions.base_recon import BaseRecon
from savu.plugins.driver.cpu_plugin import CpuPlugin
import skimage.transform as transform
import numpy as np
from scipy import ndimage
from savu.plugins.utils import register_plugin
[docs]@register_plugin
class ScikitimageFilterBackProjection(BaseRecon, CpuPlugin):
def __init__(self):
logging.debug("initialising Scikitimage Filter Back Projection")
logging.debug("Calling super to make sure that all superclasses are " +
" initialised")
super(ScikitimageFilterBackProjection,
self).__init__("ScikitimageFilterBackProjection")
def _shift(self, sinogram, centre_of_rotation):
centre_of_rotation_shift = (sinogram.shape[0] // 2) - centre_of_rotation
result = ndimage.interpolation.shift(sinogram,
(centre_of_rotation_shift, 0))
return result
[docs] def process_frames(self, data):
sino = data[0]
centre_of_rotations, angles, vol_shape, init = self.get_frame_params()
in_pData = self.get_plugin_in_datasets()[0]
sinogram = np.swapaxes(sino, 0, 1)
sinogram = self._shift(sinogram, centre_of_rotations)
dim_detX = in_pData.get_data_dimension_by_axis_label('detector_x')
size = self.parameters['output_size']
size = in_pData.get_shape()[dim_detX] if size == 'auto' or \
size is None else size
result = \
transform.iradon(sinogram, theta=angles,
output_size=(size),
filter_name=self.parameters['filter'],
interpolation=self.parameters['interpolation'],
circle=self.parameters['circle'])
return result
[docs] def get_max_frames(self):
return 'single'