adler-j

import numpy as np
import scipy as sp
import odl
from scipy import signal


class Convolve(odl.Operator):
    def __init__(self, space, kernel):
        super(Convolve, self).__init__(domain=space, range=space,
                                       linear=True)

adler-j

"""Noise-free reconstruction.

Adapted from
https://github.com/odlgroup/odl/blob/master/examples/solvers/douglas_rachford_pd_tomography_tv.py
"""

import odl
from odl.contrib.fom import psnr

# Create ODL data structures

adler-j

# http://stackoverflow.com/questions/39921607/tensorflow-how-to-make-a-custom-activation-function-with-only-python

import tensorflow as tf
from tensorflow.python.framework import ops
import numpy as np
import odl

matrix = np.array([[1, 2],
                   [0, 0],
                   [0, 1]], dtype='float32')

adler-j

import numpy as np
import odl


# --- Set-up geometry of the problem --- #


# Discrete reconstruction space: discretized functions on the rectangle
# [-20, 20]^2 with 300 samples per dimension.
reco_space = odl.uniform_discr(

adler-j

import odl
import numpy as np


class L2SquaredSmart(odl.solvers.Functional):
    def __init__(self, op, data):
        self.data = data
        self.op = op
        self.optdata = op.adjoint(data)

adler-j

#!/bin/bash
#set -x 
 
# Shows you the largest objects in your repo's pack file.
# Written for osx.
#
# @see https://stubbisms.wordpress.com/2009/07/10/git-script-to-show-largest-pack-objects-and-trim-your-waist-line/
# @author Antony Stubbs
 
export LC_ALL=C

adler-j

import fnmatch
import os

matches = []
for root, dirnames, filenames in os.walk('E:/Github/ODL/odl'):
    for filename in fnmatch.filter(filenames, '*.py'):
        matches.append(os.path.join(root, filename))
        
for match in matches:
    with open(match) as f:

adler-j

# Copyright 2014-2016 The ODL development group
#
# This file is part of ODL.
#
# ODL is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# ODL is distributed in the hope that it will be useful,

adler-j

"""Example of using the boolean ray transform with ODL.

This example is with the 2d ray transform, but you could easily change the
geometry to 3d and get the example you gave. See

github.com/odlgroup/odl/blob/master/examples/tomo/ray_trafo_parallel_3d.py

for an example.

Note that some rounding errors may occur.

adler-j

import odl
import numpy as np

# Discrete reconstruction space: discretized functions on the rectangle
# [-20, 20]^2 with 300 samples per dimension.
reco_space = odl.uniform_discr(
    min_pt=[-1, -1], max_pt=[1, 1], shape=[256, 256])

# Make a parallel beam geometry with flat detector