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tomo_operators.py
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tomo_operators.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright 2015 Pierre Paleo <pierre.paleo@esrf.fr>
# License: BSD 2-clause Simplified
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
from __future__ import division
import numpy as np
import astra
class AstraToolbox:
def __init__(self, n_pixels, n_angles, rayperdetec=None):
'''
Initialize the ASTRA toolbox with a simple parallel configuration.
The image is assumed to be square, and the detector count is equal to the number of rows/columns.
'''
self.vol_geom = astra.create_vol_geom(n_pixels, n_pixels)
self.proj_geom = astra.create_proj_geom('parallel', 1.0, n_pixels, np.linspace(0,np.pi,n_angles,False))
self.proj_id = astra.create_projector('cuda', self.proj_geom, self.vol_geom)
#~ self.rec_id = astra.data2d.create('-vol', self.vol_geom)
def backproj(self, sino_data, filt=False):
if filt is True:
bid, rec = astra.create_backprojection(self.filter_projections(sino_data), self.proj_id)#,useCUDA=True) #last keyword for astra 1.1
else:
bid, rec = astra.create_backprojection(sino_data, self.proj_id)#,useCUDA=True) #last keyword for astra 1.1
astra.data2d.delete(bid)
return rec
def proj(self, slice_data):
sid, proj_data = astra.create_sino(slice_data, self.proj_id)
astra.data2d.delete(sid)
return proj_data
def filter_projections(self, proj_set):
nb_angles, l_x = proj_set.shape
ramp = 1./l_x * np.hstack((np.arange(l_x), np.arange(l_x, 0, -1)))
return np.fft.ifft(ramp * np.fft.fft(proj_set, 2*l_x, axis=1), axis=1)[:,:l_x].real
def cleanup(self):
#~ astra.data2d.delete(self.rec_id)
astra.data2d.delete(self.proj_id)