def test_synthetic_volumetric_data_generation(self):
"""
Generovani umeleho stromu do 3D a jeho evaluace.
V testu dochazi ke kontrole predpokladaneho objemu a deky cev
"""
# from skelet3d.tree import TreeGenerator
# from fibrous.tree import TubeSkeletonBuilder as TreeGenerator
# from fibrous.tree import TreeBuilder as TreeGenerator
from fibrous.tb_volume import TBVolume as TreeGenerator
# print("zacatek podezreleho testu")
# import segmentation
# import misc
# generate 3d data from yaml for testing
tvg = TreeGenerator()
yaml_path = os.path.join(path_to_script, "./hist_stats_test.yaml")
tvg.importFromYaml(yaml_path)
tvg.set_area_sampling(voxelsize_mm=[1, 1, 1], shape=[100, 101, 102])
# tvg.voxelsize_mm = [1, 1, 1]
# tvg.shape = [100, 100, 100]
# data3d = tvg.generateTree()
data3d = tvg.buildTree()
self.assertEqual(data3d.shape[0], 100)
self.assertEqual(data3d.shape[1], 101)
self.assertEqual(data3d.shape[2], 102)
def test_surface_measurement_find_edge(self):
tvg = TBVolume()
yaml_path = os.path.join(path_to_script, "./hist_stats_test.yaml")
tvg.importFromYaml(yaml_path)
tvg.voxelsize_mm = [1, 1, 1]
tvg.shape = [100, 100, 100]
data3d = tvg.buildTree()
self.assertGreater(np.sum(data3d), 10, "Image should be not empty")
def test_import_new_vt_format(self):
# tvg = TreeBuilder()
tvg = TBVolume()
yaml_path = os.path.join(path_to_script, "vt_biodur_simple.yaml")
tvg.importFromYaml(yaml_path)
tvg.set_area_sampling(voxelsize_mm=[1,1,1], shape=[150, 150, 150])
# tvg.voxelsize_mm = [1, 1, 1]
# tvg.shape = [150, 150, 150]
data3d = tvg.buildTree()
def test_get_tree_simple(self):
from fibrous.tb_volume import TBVolume
tvg = TBVolume()
yaml_path = os.path.join(path_to_script, "./hist_stats_test.yaml")
tvg.importFromYaml(yaml_path)
# tvg.init_data3d(shape=[100, 100, 100])
# output = tvg.buildTree() # noqa
from fibrous.tb_vtk import gen_tree_simple
# from fibrous.tree import single_tree_compatibility_to_old
vtk_tree = gen_tree_simple(tvg.tube_skeleton)
self.assertTrue(vtk_tree is not None)
def test_vessel_tree_volume_with_new_subclass(self):
from fibrous.tb_volume import TBVolume
tvg = TBVolume()
yaml_path = os.path.join(path_to_script, "./hist_stats_test.yaml")
tvg.importFromYaml(yaml_path)
tvg.init_data3d(shape=[100, 100, 100])
output = tvg.buildTree() # noqa
# import sed3
# ed = sed3.sed3(output)
# ed.show()
self.assertEqual(output[50, 20, 20], 200)
self.assertEqual(output[5, 5, 5], 20)
def test_surface_measurement_find_edge(self):
import imtools.surface_measurement as sm
tvg = TBVolume()
yaml_path = os.path.join(path_to_script, "./hist_stats_test.yaml")
tvg.importFromYaml(yaml_path)
tvg.voxelsize_mm = [1, 1, 1]
tvg.shape = [100, 100, 100]
data3d = tvg.buildTree()
# init histology Analyser
# metadata = {'voxelsize_mm': tvg.voxelsize_mm}
# data3d = data3d * 10
# threshold = 2.5
im_edg = sm.find_edge(data3d, 0)
# in this area should be positive edge
self.assertGreater(np.sum(im_edg[25:30, 25:30, 30]), 3)
def test_synthetic_volumetric_data_generation():
"""
Generovani umeleho stromu do 3D a jeho evaluace.
V testu dochazi ke kontrole predpokladaneho objemu a deky cev
"""
# from skelet3d.tree import TreeGenerator
# from fibrous.tree import TubeSkeletonBuilder as TreeGenerator
# from fibrous.tree import TreeBuilder as TreeGenerator
from fibrous.tb_volume import TBVolume as TreeGenerator
# print("zacatek podezreleho testu")
# import segmentation
# import misc
# generate 3d data from yaml for testing
tvg = TreeGenerator()
yaml_path = os.path.join(path_to_script, "./hist_stats_test.yaml")
tvg.importFromYaml(yaml_path)
tvg.set_area_sampling(voxelsize_mm=[1, 1, 1], shape=[100, 101, 102])
# tvg.voxelsize_mm = [1, 1, 1]
# tvg.shape = [100, 100, 100]
# data3d = tvg.generateTree()
data3d = tvg.buildTree()
assert data3d.shape[0] == 100
assert data3d.shape[1] == 101
assert data3d.shape[2] == 102
# plt.imshow(data3d[:,:,50])
# plt.colorbar()
# plt.show()
io3d.write(data3d.astype(np.uint8), path="./slice{:04d}.jpg")
# self.assertEqual(data3d.shape[0], 100)
# self.assertEqual(data3d.shape[1], 101)
# self.assertEqual(data3d.shape[2], 102)
tvg = TreeGenerator()
yaml_path = os.path.join(path_to_script, "./hist_stats_test.yaml")
tvg.importFromYaml(yaml_path)
tvg.set_area_sampling(voxelsize_mm=[0.5, 0.5, 0.5], shape=[100, 101, 102])
io3d.write(data3d.astype(np.uint8), path="./ssslice{:04d}.jpg")