test/test_tomopy/test_recon/test_algorithm.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
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from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import unittest
from ..util import read_file
from tomopy.recon.algorithm import recon
from numpy.random import default_rng
from numpy.testing import assert_allclose
import numpy as np
__author__ = "Doga Gursoy"
__copyright__ = "Copyright (c) 2015, UChicago Argonne, LLC."
__docformat__ = 'restructuredtext en'
try:
import mkl_fft
found_mkl = True
except ImportError:
found_mkl = False
try:
import cv2
found_opencv = True
except ImportError:
found_opencv = False
class ReconstructionAlgorithmTestCase(unittest.TestCase):
def setUp(self):
self.prj = read_file('proj.npy')
self.ang = read_file('angle.npy').astype('float32')
def test_art(self):
os.environ["TOMOPY_USE_C_ART"] = "1"
assert_allclose(recon(self.prj, self.ang, algorithm='art', num_iter=4),
read_file('art.npy'),
rtol=1e-2)
def test_bart(self):
rng = default_rng(0)
ind_block = np.arange(len(self.ang))
rng.shuffle(ind_block)
assert_allclose(
recon(
self.prj,
self.ang,
algorithm='bart',
num_iter=4,
num_block=3,
ind_block=ind_block,
),
read_file('bart.npy'),
rtol=1e-2,
atol=1e-5,
)
def test_fbp(self):
assert_allclose(recon(self.prj, self.ang, algorithm='fbp'),
read_file('fbp.npy'),
rtol=1e-2)
def test_gridrec_custom(self):
assert_allclose(
recon(self.prj, self.ang, algorithm='gridrec', filter_name='none'),
recon(self.prj,
self.ang,
algorithm='gridrec',
filter_name='custom',
filter_par=np.ones(self.prj.shape[-1], dtype=np.float32)))
def test_gridrec(self):
assert_allclose(recon(self.prj,
self.ang,
algorithm='gridrec',
filter_name='none'),
read_file('gridrec_none.npy'),
rtol=1e-2)
assert_allclose(recon(self.prj,
self.ang,
algorithm='gridrec',
filter_name='shepp'),
read_file('gridrec_shepp.npy'),
rtol=1e-2)
assert_allclose(recon(self.prj,
self.ang,
algorithm='gridrec',
filter_name='cosine'),
read_file('gridrec_cosine.npy'),
rtol=1e-2)
assert_allclose(recon(self.prj,
self.ang,
algorithm='gridrec',
filter_name='hann'),
read_file('gridrec_hann.npy'),
rtol=1e-2)
assert_allclose(recon(self.prj,
self.ang,
algorithm='gridrec',
filter_name='hamming'),
read_file('gridrec_hamming.npy'),
rtol=1e-2)
assert_allclose(recon(self.prj,
self.ang,
algorithm='gridrec',
filter_name='ramlak'),
read_file('gridrec_ramlak.npy'),
rtol=1e-2)
assert_allclose(recon(self.prj,
self.ang,
algorithm='gridrec',
filter_name='parzen'),
read_file('gridrec_parzen.npy'),
rtol=1e-2)
assert_allclose(recon(self.prj,
self.ang,
algorithm='gridrec',
filter_name='butterworth'),
read_file('gridrec_butterworth.npy'),
rtol=1e-2)
def test_mlem(self):
result = recon(self.prj, self.ang, algorithm='mlem', num_iter=4)
assert_allclose(result, read_file('mlem.npy'), rtol=1e-2)
@unittest.skipUnless(found_opencv, "CPU acceleration requires OpenCV.")
def test_mlem_accel(self):
result = recon(self.prj,
self.ang,
algorithm='mlem',
num_iter=4,
accelerated=True,
device='cpu',
ncore=1,
pool_size=3)
assert_allclose(result, read_file('mlem_accel.npy'), rtol=1e-2)
@unittest.skipUnless("CUDA_VERSION" in os.environ, "CUDA_VERSION not set.")
def test_mlem_gpu(self):
result = recon(self.prj,
self.ang,
algorithm='mlem',
num_iter=4,
accelerated=True,
device='gpu',
ncore=1,
pool_size=3)
assert_allclose(result, read_file('mlem_accel_gpu.npy'), rtol=1e-2)
def test_osem(self):
rng = default_rng(0)
ind_block = np.arange(len(self.ang))
rng.shuffle(ind_block)
assert_allclose(
recon(
self.prj,
self.ang,
algorithm='osem',
num_iter=4,
num_block=3,
ind_block=ind_block,
),
read_file('osem.npy'),
rtol=1e-2,
atol=1e-5,
)
def test_ospml_hybrid(self):
rng = default_rng(0)
ind_block = np.arange(len(self.ang))
rng.shuffle(ind_block)
assert_allclose(
recon(
self.prj,
self.ang,
algorithm='ospml_hybrid',
num_iter=4,
num_block=3,
ind_block=ind_block,
),
read_file('ospml_hybrid.npy'),
rtol=1e-2,
atol=1e-5,
)
def test_ospml_quad(self):
rng = default_rng(0)
ind_block = np.arange(len(self.ang))
rng.shuffle(ind_block)
assert_allclose(
recon(
self.prj,
self.ang,
algorithm='ospml_quad',
num_iter=4,
num_block=3,
ind_block=ind_block,
),
read_file('ospml_quad.npy'),
rtol=1e-2,
atol=1e-5,
)
def test_pml_hybrid(self):
assert_allclose(
recon(self.prj, self.ang, algorithm='pml_hybrid', num_iter=4),
read_file('pml_hybrid.npy'),
rtol=1e-2,
)
def test_pml_quad(self):
assert_allclose(
recon(self.prj, self.ang, algorithm='pml_quad', num_iter=4),
read_file('pml_quad.npy'),
rtol=1e-2,
)
def test_sirt(self):
result = recon(self.prj, self.ang, algorithm='sirt', num_iter=4)
assert_allclose(result, read_file('sirt.npy'), rtol=1e-2)
@unittest.skipUnless(found_opencv, "CPU acceleration requires OpenCV.")
def test_sirt_accel(self):
result = recon(self.prj,
self.ang,
algorithm='sirt',
num_iter=4,
accelerated=True,
device='cpu',
ncore=1,
pool_size=3)
assert_allclose(result, read_file('sirt_accel.npy'), rtol=1e-2)
@unittest.skipUnless("CUDA_VERSION" in os.environ, "CUDA_VERSION not set.")
def test_sirt_gpu(self):
result = recon(self.prj,
self.ang,
algorithm='sirt',
num_iter=4,
accelerated=True,
device='gpu',
ncore=1,
pool_size=3)
assert_allclose(result, read_file('sirt_accel_gpu.npy'), rtol=1e-2)
def test_tv(self):
assert_allclose(recon(self.prj, self.ang, algorithm='tv', num_iter=4),
read_file('tv.npy'),
rtol=1e-2)
def test_grad(self):
assert_allclose(recon(self.prj, self.ang, algorithm='grad',
num_iter=4),
read_file('grad.npy'),
rtol=1e-2)
def test_tikh(self):
assert_allclose(recon(self.prj, self.ang, algorithm='tikh',
num_iter=4),
read_file('tikh.npy'),
rtol=1e-2)