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Reduce runtime of radon test cases

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This commit is contained in:
Johannes Schönberger
2013-11-09 23:31:01 +01:00
parent f651cba56e
commit f8a0fcbc2a
1 changed files with 14 additions and 21 deletions
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skimage/transform/tests/test_radon_transform.py
+14 -21
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@@ -5,17 +5,14 @@ from numpy.testing import assert_raises
import itertools
import os.path
from skimage.transform import radon, iradon
from skimage.transform import radon, iradon, iradon_sart, rescale
from skimage.io import imread
from skimage import data_dir
__PHANTOM = imread(os.path.join(data_dir, "phantom.png"),
PHANTOM = imread(os.path.join(data_dir, "phantom.png"),
as_grey=True)[::2, ::2]
def _get_phantom():
return __PHANTOM
PHANTOM = rescale(PHANTOM, 0.5, order=1)
def _debug_plot(original, result, sinogram=None):
@@ -39,7 +36,7 @@ def _debug_plot(original, result, sinogram=None):
plt.show()
def rescale(x):
def _rescale_intensity(x):
x = x.astype(float)
x -= x.min()
x /= x.max()
@@ -117,7 +114,7 @@ def test_iradon_center():
def check_radon_iradon(interpolation_type, filter_type):
debug = False
image = _get_phantom()
image = PHANTOM
reconstructed = iradon(radon(image), filter=filter_type,
interpolation=interpolation_type)
delta = np.mean(np.abs(image - reconstructed))
@@ -128,7 +125,7 @@ def check_radon_iradon(interpolation_type, filter_type):
if interpolation_type == 'nearest':
allowed_delta = 0.03
else:
allowed_delta = 0.02
allowed_delta = 0.025
else:
allowed_delta = 0.05
assert delta < allowed_delta
@@ -156,7 +153,7 @@ def test_iradon_angles():
radon_image_200 = radon(image, theta=np.linspace(0, 180, nb_angles,
endpoint=False))
reconstructed = iradon(radon_image_200)
delta_200 = np.mean(abs(rescale(image) - rescale(reconstructed)))
delta_200 = np.mean(abs(_rescale_intensity(image) - _rescale_intensity(reconstructed)))
assert delta_200 < 0.03
# Lower number of projections
nb_angles = 80
@@ -225,7 +222,7 @@ def test_radon_circle():
r = np.sqrt((c0 - shape[0] // 2)**2 + (c1 - shape[1] // 2)**2)
radius = min(shape) // 2
image = np.clip(radius - r, 0, np.inf)
image = rescale(image)
image = _rescale_intensity(image)
angles = np.linspace(0, 180, min(shape), endpoint=False)
sinogram = radon(image, theta=angles, circle=True)
assert np.all(sinogram.std(axis=1) < 1e-2)
@@ -314,14 +311,9 @@ def test_order_angles_golden_ratio():
def test_iradon_sart():
from skimage.io import imread
from skimage import data_dir
from skimage.transform import rescale, radon, iradon_sart
debug = False
shepp_logan = imread(os.path.join(data_dir, "phantom.png"), as_grey=True)
image = rescale(shepp_logan, scale=0.4)
image = rescale(PHANTOM, 0.8)
theta_ordered = np.linspace(0., 180., image.shape[0], endpoint=False)
theta_missing_wedge = np.linspace(0., 150., image.shape[0], endpoint=True)
for theta, error_factor in ((theta_ordered, 1.),
@@ -344,15 +336,15 @@ def test_iradon_sart():
delta = np.mean(np.abs(reconstructed - image))
print('delta (1 iteration) =', delta)
assert delta < 0.016 * error_factor
assert delta < 0.02 * error_factor
reconstructed = iradon_sart(sinogram, theta, reconstructed)
delta = np.mean(np.abs(reconstructed - image))
print('delta (2 iterations) =', delta)
assert delta < 0.013 * error_factor
assert delta < 0.014 * error_factor
reconstructed = iradon_sart(sinogram, theta, clip=(0, 1))
delta = np.mean(np.abs(reconstructed - image))
print('delta (1 iteration, clip) =', delta)
assert delta < 0.015 * error_factor
assert delta < 0.018 * error_factor
np.random.seed(1239867)
shifts = np.random.uniform(-3, 3, sinogram.shape[1])
@@ -377,7 +369,8 @@ def test_iradon_sart():
delta = np.mean(np.abs(reconstructed - image))
print('delta (1 iteration, shifted sinogram) =', delta)
assert delta < 0.018 * error_factor
assert delta < 0.022 * error_factor
if __name__ == "__main__":
from numpy.testing import run_module_suite